NASA/Goddard Space Flight Center

Earth Observing System

January 1999
EOS

Editors

Design and Production

Reynold Greenstone

Raytheon ITSS

Michael D. King

NASA/Goddard Space Flight Center

Sterling Spangler

Raytheon ITSS

Plan

Science

Executive

Summary
Table of Contents

Foreword 4

Special Note about the Summary 5

Chapter 1 Summary 7

Overview

Chapter 2 Summary 11

Radiation, Clouds, Water Vapor, Precipitation,

and Atmospheric Circulation

Chapter 3 Summary 24

Ocean Circulation, Productivity, and Exchange

with the Atmosphere

Chapter 4 Summary 28

Atmospheric Chemistry and Greenhouse Gases

Chapter 5 Summary 32

Land Ecosystems and Hydrology

Chapter 6 Summary 35

Cryospheric Systems

Chapter 7 Summary 42

Ozone and Stratospheric Chemistry

Chapter 8 Summary 46

Volcanoes and Climate Effects of Aerosols

Acronyms 51

Index 57
4 EOS SCIENCE PLAN

Foreword

From the dawn of space exploration NASA has been in the forefront of providing the unique vantage point of

space as an ideal setting for observing Earth as a whole system consisting of atmosphere, oceans, and continents capable of supporting life in our solar system. Today, NASA continues to sponsor research and development towards understanding the origins of life in the universe. The best proxy for this search and discover

mission is life on Earth, and the NASA Earth Science Enterprise captures the spirit of exploration and focuses

it back on our home planet. But this requires understanding Earth as an integrated system of atmosphere, land,

oceans, and life, which has evolved in the past and will continue to evolve in the future. Building on our

observations of the Earth since the earliest days of the space program—NASA built the first weather and land

observing satellites—we are using orbiting spacecraft to bring congruency to multiple disciplines within Earth

sciences through integrated observations, interdisciplinary scientific research and analysis, and modeling. This

is the blueprint for the Earth Science Enterprise at NASA and its Earth Observing System (EOS) program.

The EOS program was established in 1991 as a U.S. Presidential initiative to provide in-depth scientific

understanding about the functioning of Earth as a system. It was envisioned that such scientific knowledge

would provide the foundation for understanding the natural and human-induced variations in Earth’s climate

system and also provide a sound basis for environmental policy decision making. Beyond scientific discovery

and explorations, it was also envisioned that EOS would have practical societal benefits in the form of providing scientific knowledge toward the efficient production of food and fiber, management of fresh water resources, and improvement of air quality. Less than a decade later, EOS is now a reality and delivering on its

promises. During the first phase of the EOS program NASA is funding the development and launch of 25

satellites, and a uniquely comprehensive Earth observations-related data and information system. Hundreds of

Earth scientists and engineers are supported, and more than 350 students per year are pursuing graduate

degrees in Earth science with NASA funding.

The EOS Science Plan is the product of several years of discussion and debate among the EOS investigators.

The considerable time required to develop this document should be viewed as a major strength because of the

deep-rooted commitments of the contributors to this document and their ability to deliver on their promise. The

objective of this Plan is to convey how EOS investigators plan to utilize the space-based and in situ observations along with modeling and data analysis methods/techniques to address the EOS scientific and applications

objectives. Therefore, the principal intended audience for this plan is the body of international Earth scientists

and science program directors. Given the complexity of the task at hand and the level of details that had to be

provided, the Pan became more than 350 pages long. A short version of the Plan has also been developed in the

form of an Executive Summary. We believe that these two documents will be seen to be an effective means of

communicating the scientific priorities of the EOS program and how NASA and EOS investigators plan to

implement these priorities during the next 5-7 years.

As we move towards the next century the changing Earth’s environment will be the focus of many agricultural,

industrial, and societal concerns and policy decisions. NASA’s Earth Science Enterprise is committed to timely

provision of the scientific knowledge needed by world leaders to formulate sound and equitable environmental

decisions.

Ghassem R. Asrar

Associate Administrator

Office of Earth Science

NASA Headquarters

Washington, D.C.
Executive Summary 5

Special Note about the Summary

The EOS Science Plan is a lengthy document that describes in great detail the state of the science

being investigated by participants in NASA’s Earth Observing System (EOS). This Executive Summary has been prepared as a companion document that summarizes all of the elements of the full

Science Plan, but sacrifices the degree of detail that appears in the full document. Both in this companion document and in the full document, readers will find presentations on the nature of the EOS

Program and the background of concerns and recommendations that led to its formation.

This Executive Summary contains an overview chapter provided by E. J. Barron and then seven

topical science chapters as follows:

2. Radiation, clouds, water vapor, precipitation, and atmospheric circulation

 D. L. Hartmann – University of Washington

3. Ocean circulation, productivity, and exchange with the atmosphere

 D. A. Rothrock – University of Washington

4. Atmospheric chemistry and greenhouse gases

 D. Schimel – National Center for Atmospheric Research

5. Land ecosystems and hydrology

 S. W. Running – University of Montana

 G. J. Collatz – Goddard Space Flight Center

 J. Washburne – University of Arizona

 S. Sorooshian – University of Arizona

6. Cryospheric systems

 B. E. Goodison – Atmospheric Environment Service, Canada

 R. D. Brown – Atmospheric Environment Service, Canada

 R. G. Crane – The Pennsylvania State University

7. Ozone and stratospheric chemistry

 M. R. Schoeberl – Goddard Space Flight Center

8. Volcanoes and climate effects of aerosol

 D. L. Hartmann – University of Washington

 P. Mouginis-Mark – University of Hawaii
6 EOS SCIENCE PLAN

Readers wishing more details about the IDS investigations or the planned EOS spacecraft missions

and the instruments they will carry are advised to consult the 1999 edition of the Earth Science

Enterprise/EOS Reference Handbook. The handbook also provides the names of all IDS principal

investigators and co-investigators as well as the names of the EOS instrument team leaders, team

members, principal investigators, and co-investigators. An excellent way to keep current with EOS

developments is to consult the EOS Project Science Office website at http://eos.nasa.gov/.

It should be noted that EOS is a fluid program, with changes in long-term plans always a possibility due to new scientific developments or to budgetary considerations. Authors and editors have

tried to keep abreast of changes in mission and instrument names, but some of the older terminology may not have been caught in every instance. For this we apologize.

Acknowledgments

Special thanks go to D. A. Rothrock, University of Washington, who provided the outline for all

the topical science chapters, and thus, in a sense, gave the necessary impetus to the launching of

this plan. Much of the technical material in the plan was provided not only by the listed lead

authors and named contributors, but also by many other unnamed EOS scientists and engineers.

R. Greenstone and W. R. Bandeen (both of Raytheon Corporation) provided technical editing

throughout the lengthy process of assembling and refining in standard format the text and appendices of this plan. Design and layout of the plan were the work of Sterling Spangler (also of

Raytheon Corporation).

-Michael D. King

EOS Senior Project Scientist

January 1999
Chapter 1 Executive Summary 7

Chapter 1

EOS Science Plan Overview

Introduction

Chapter 1, as its name implies, gives an overview of the seven topical science chapters that follow. In addition, it provides some of the background that has led up to

the establishment of NASA’s Earth Observing System. In succeeding sections EOS

support to various field campaigns is presented, and the measurement strategy that

has been adopted for EOS is explained. The chapter ends with a presentation on

EOS contributions to national goals and needs related to global change and a summary that brings out the critical role of EOS in addressing the key challenge to

develop the capability to predict the changes that will occur in the next decade to

century, both naturally and in response to human activity.

Impetus for EOS

The development of EOS can be traced back to 1979 and the establishment of the

World Climate Research Program, which was an international effort to understand

the physical basis of climate in response to droughts and floods that revealed societal vulnerability to climate variability. In the following years it began to be

recognized that an integrated programmatic framework would have to be the central paradigm of both national and international programs that would be able to

understand global change. Starting in 1985, a series of National Research Council

reports called for an observing strategy that would focus on the highest priority

measurements needed for each of the major disciplines of the Earth sciences. The

reports stressed the need for simultaneity, calibration, and continuity of measurements to show how the Earth is changing and to develop and validate global

predictive models. The Earth System Sciences Committee (ESSC), formed at

NASA’s behest, in 1988 called for a program of sustained long-term measurements

of global variables. The Committee stressed that the measurements must be coupled

to focused process studies and the development of Earth system models. The program must also include an information system that would ensure open access to

consistent, long-term observations of the Earth system.

Now EOS is an integral element of the U.S. Global Change Research Program (USGCRP). Four key USGCRP global change issues are: 1)

seasonal-to-interannual climate variability, 2) climate change over decades to centuries, 3) changes in ozone, ultraviolet radiation, and atmospheric chemistry, and 4)

changes in land cover and in terrestrial and aquatic systems. In addition to these

areas of particular scientific and practical importance, USGCRP has defined an

overarching objective (often referred to as “human dimension”) to identify, understand, and analyze how human activities contribute to changes in natural systems,
8 EOS SCIENCE PLAN

how the consequences of natural and human-induced change affect the health and

well-being of humans and their institutions, and how humans could respond to problems associated with environmental change.

EOS science in support of the USGCRP is well described by the seven

topical science chapters presented in this EOS Science Plan: Radiation, clouds,

water vapor, precipitation, and atmospheric circulation; Ocean circulation, productivity, and exchange with the atmosphere; Atmospheric chemistry and greenhouse

gases; Land ecosystems and hydrology; Cryospheric systems; Ozone and stratospheric chemistry; and Volcanoes and climate effects of aerosols.

EOS Science Contributions

EOS science contributions are too numerous to present in detail in this summary,

but can be viewed for convenience as a means of obtaining global measurements

(with appropriate characteristics) of the 24 variables listed in a table on the following page.

As pointed out in the text, EOS observations related to atmospheric phenomena will provide for validation on scales ranging from the size of cloud systems

to regional to global and will support modeling efforts at these spatial scales as well

as temporal scales ranging, correspondingly, from less than a day, to ten days, to

100 years. Several EOS interdisciplinary investigations are pursuing improved understanding of cloud-climate feedbacks where great uncertainties exist for predictions

of climate change.

EOS measurements will shed new light on both physical and biological

aspects of the world’s oceans, including their circulation, their productivity, and

their role in exchanging gases such as carbon dioxide with the atmosphere. EOS

observations related to greenhouse gases and the chemistry of the lower atmosphere

will lead to new understanding of the events that control the production of tropospheric ozone including the occurrence of biomass burning and the changes in land

cover that are taking place worldwide.

EOS measurements of land ecosystems and hydrology will provide unprecedented worldwide coverage of vegetation extent and characteristics, thus

improving our knowledge of terrestrial biospheric dynamics and vegetation process activity. Long-term consistent data sets related to the cryosphere will be able

to document changes and validate transient model simulations using global climate

models. EOS laser altimetry through repeated measurements will reveal changes in

the surface elevation of ice sheets, and thereby improve our knowledge of changes

in their mass balance with implications for sea-level rise.

EOS will contribute greatly, through measurements of trace gas chemistry

and temperatures in the stratosphere, to our understanding of changes in the ozone

layer and the related climate forcing. EOS will enable the first truly global inventory of volcanic eruptions with their implications for climate change through the

introduction of stratospheric aerosols. In addition, timely EOS observations of volcanic phenomena can lead to significant warnings of hazards for people on the

ground or for aircraft that may encounter volcanic plumes or clouds, possibly causing the aircraft to crash.
Chapter 1 Executive Summary 9

24 EOS Measurements
10 EOS SCIENCE PLAN

National and International Contributions to Major Field

Campaigns

EOS observations and modeling studies clearly will support numerous surface observation efforts and many major field campaigns. Just to list a few of these, there

are the Global Energy and Water Cycle Experiment (GEWEX) , the Climate Variability project (CLIVAR) of the World Climate Research Program, and the Joint

Global Ocean Flux Study (JGOFS) of the International Geosphere-Biosphere Program (IGBP)

EOS Measurement Strategy

EOS has developed a measurement strategy that includes:

• Simultaneity of observations taken by a group of sensors preferably on the same

satellite platform or else closely coordinated in space and time;

• Overlap between measurements by successive sensors for intercomparison and

intercalibration, in order to construct useful long-term climate records;

• Diurnal sampling to detect changes of rapidly varying systems such as clouds;

• High-quality calibration to permit intra- and intersystem data comparisons; and

• A data continuity strategy that ensures that successive sensors will maintain a

data stream for long-term analyses of changing phenomena.

EOS Contributions to National Goals and Needs

 The remainder of this chapter is devoted to a demonstration of the response of EOS

to “National Goals and Needs” as defined by the five USGCRP themes presented at

the beginning of this summary. For each theme, “the national interest” is presented

along with the related “national policy requirements,” and then the “EOS PolicyRelevant Contributions” are given in terms of measurements by the EOS sensors

and assessments based on EOS interdisciplinary studies. Notably, EOS studies will

provide a realistic basis for understanding the potential rate and magnitude of global change in all its aspects as it affects the world around us and the people of our

Earth.
Chapter 2 Executive Summary 11

Introduction

Chapter 2 focuses on the role of radiation, clouds, atmospheric water, precipitation, and atmospheric circulation in determining climate and global change.

The chapter begins with a discussion of major scientific issues involving each

of the relevant climate areas and how they affect climate. Then, for each climate area, there is a discussion of the required satellite and field measurement

programs. The chapter ends with a review of anticipated EOS contributions to

improving our knowledge of the key climate variables and data sets.

Background

The temperature near the surface of the Earth is in thermodynamic equilibrium when the absorption of radiant energy from the sun is in approximate

balance with the emission of radiant energy to space from the Earth. Thus, the

energy output of the sun provides a critical control on the Earth’s climate. The

amount of the solar energy that is absorbed by the Earth depends on Earth’s

reflectivity, and the reflectivity is strongly dependent on the fractional coverage and optical properties of clouds in the atmosphere, the amount and optical

properties of aerosol particles in the atmosphere, the atmospheric humidity,

and the condition of the surface.

The surface temperature of the Earth depends not only on the absorbed

solar radiation but also on the rate at which energy is reradiated to space from

the Earth. The rate of reradiation is controlled by both the amount and the

vertical distribution of not only the clouds and aerosol particles but also the

amount and distribution of the greenhouse gases in the atmosphere, of which

the most important is water vapor. The water vapor distribution interacts

strongly with convection in the atmosphere and the associated clouds, precipitation, and large-scale circulations. The water vapor distribution also

interacts strongly with the thermal structure of the atmosphere.

Understanding the interactions among the various elements listed above

and incorporating this understanding into appropriate models constitutes a

critical step in predicting future climate changes and their regional and global

impacts. Likewise, improved understanding in these areas will help in the

prediction of seasonal and interannual climate variability. Beyond the confines of the atmosphere there are also interactions with the oceans to be

considered, and these are strongly modulated by clouds, water vapor, and

large-scale circulations.

Chapter 2

Radiation, Clouds, Water Vapor, Precipitation,

and Atmospheric Circulation
12 EOS SCIENCE PLAN

Total Solar Irradiance

The energy from the sun that is available to be received at the average distance of

the Earth from the sun is called total solar irradiance (TSI) and is specified in watts

per square meter (Wm-2). Long-term solar monitoring from space began with the

Earth Radiation Budget (ERB) experiment in late 1978 and has continued into the

present time frame with measurements from the Active Cavity Radiometer Irradiance Monitor II (ACRIM II) on NASA’s Upper Atmosphere Research Satellite

(UARS). Consistent measurements by ACRIM instruments I and II have shown

variations in TSI running from a low of about 1367 Wm-2 at a solar cycle minimum

in 1986 to a high of about 1369 Wm-2 in 1992 at a solar cycle peak. Although these

changes appear small, it has been shown (Rind and Overpeck, 1993; Lean et al.,

1994) that sustained changes in TSI of as little as a few tenths of one percent could

be causal factors for significant climate change on time scales ranging from decades to centuries. Climate changes comparable to the “Little Ice Age” may involve

TSI changes as small as 0.5% over 200+ years.

The Role of Radiation Fluxes in the Climate System

The climate system is a heat engine that is driven by the spatial and temporal displacement of the entry and exit of broadband radiant energy. Radiation is the primary

forcing element in climate change. A net flow of radiant energy at the top of the

atmosphere enters the tropics and leaves at high latitudes. The resulting equatorto-pole heating gradient drives the circulations of the atmosphere and ocean. The

largest fraction of radiant energy entering the climate system is absorbed at the

surface in the form of solar radiation, but leaves the atmosphere in the form of

thermal infrared emission. This radiative heating below and cooling above drives

the convective activity of the troposphere, resulting in abundant rainfall and cleansing of the atmosphere.

Radiation is important for climate feedback. Uncertainties in the radiative

feedback to climate by clouds pose the most formidable obstacle to climate prediction by general circulation models (GCMs). Because of the uncertainty in the cloud/

climate feedback to changes in radiation at the top of the atmosphere (TOA) we

cannot reliably predict the climate response to a given radiative forcing. However,

there have been fairly good simulations of transient temperature variations to the

radiative forcing due to the aerosol plumes that resulted from the 1991 Mt. Pinatubo

eruption (Hansen et al., 1994).

Atmospheric gases have a greater effect on the climate than any other component of the Earth’s climate system. It is estimated that absorption of infrared

radiation by atmospheric gases reduces the escaping longwave radiation by about

120 Wm-2, whereas the reflection of solar radiation by clouds and the surface each

return only about 50 Wm-2 to space, when globally averaged. Modern climate models

have consistently indicated that CO2 and other anthropogenic traces gases will

change the vertical distribution of radiative fluxes in the atmospheric column so as

to warm the troposphere and cool the stratosphere.

Top-of-the-atmosphere shortwave and longwave radiative fluxes are used

to derive surface radiative fluxes. Currently available results from the Earth Radia-
Chapter 2 Executive Summary 13

tion Budget Experiment (ERBE) seem to have an error of about 5 Wm-2 , which

presumably contributes to even larger errors in surface radiative fluxes.

EOS will contribute to improved understanding of the effects of the atmospheric gases by producing more-accurate vertical profiles and time histories of

water vapor and radiative active gases and by validating the radiative transfer physics for both the natural and anthropogenic gases in the atmosphere. Ellingson et al.

(1991) have shown that there are still significant problems with the calculation of

broadband radiative fluxes in the atmosphere for a given distribution of atmospheric

gases.

Both the direct and indirect radiative effects of aerosols constitute the largest

uncertainties in the anthropogenic radiative forcing of climate. Anthropogenic sulfate aerosols mostly scatter shortwave radiation and cool the climate. Smoke from

biomass burning may have a global cooling effect of 0.2 to 2 Wm-2 .

Clouds are second only to greenhouse gases in terms of their effect on climate. However, there is great uncertainty about cloud radiative forcing and feedback

(Cess et al., 1991). Estimating the radiative effects of clouds and retrieving cloud

properties from space both require a detailed understanding of the scattering and

absorption properties of clouds. Important problems remain in modeling the directional scattering of solar radiation by clouds, the radiative effects of the overlap of

cloud fragments, and perhaps even in the basic absorption properties of cloudy

atmospheres. The EOS instrument CERES, along with other EOS instruments such

as MISR and EOSP, is expected to provide significant advances in the estimate of

radiative forcing by clouds. EOS will begin to resolve problems caused by cloud

overlap and cloud geometrical thickness through use of both passive and active

sensors.

The long homogeneous record of clouds and radiation fluxes to be provided

by EOS in the course of 15-18 years of observations will allow seasonal and

interannual variability to be sampled adequately and will be used to understand

connections within the climate system that only appear on longer time scales.

The surface of the Earth absorbs about twice as much solar radiation as does

the atmospheric column above. The amount of solar radiation that is absorbed by

the surface is modulated by a surface solar albedo that ranges from 0.06 for diffuse

radiation striking the ocean to approximately 0.90 for some of the freshest snow.

The GEWEX Surface Radiation Budget (SRB) Project has found that errors in both

shortwave and longwave radiation over snow and ice surfaces and for longwave

radiation in persistently cloudy regions are larger than those in other regions. There

are problems in satellite determinations that require distinguishing between clouds

and snow-covered surfaces. Surface albedos and radiative fluxes over snow-free

land are also not known to sufficient accuracy. Until EOS determines the surface

albedo of all land surfaces to greater accuracy, it will not be possible to quantify

adequately the radiative forcing to climate that is associated with changes in land

use.

The surface energy budget provides a key forcing to ocean circulation so

that more-accurate information is needed in this aspect of radiation studies as well.

Downwelling longwave radiation measurements over the extratropical oceans will
14 EOS SCIENCE PLAN

be a limiting factor for EOS sensors. The retrieval of this radiation will be improved by combining satellite measurements with data from ocean-based monitoring

stations that would provide both surface radiation budget and cloud-base heights.

The Role of Convection and Clouds in Climate

Clouds not only affect the radiative energy fluxes in the atmosphere through scattering, absorption, and reradiation but also vertical motions associated with them

produce important convective transports of energy and moisture. Interactions of

clouds with the clear environment around them play a critical role in determining

both the amount of water vapor that is retained in the clear atmosphere and the

amount of precipitation reaching the surface. The influence of clouds on the radiation balance of the Earth was estimated by the Earth Radiation Budget Experiment

(ERBE; Ramanathan et al., 1989; Harrison et al., 1990). These estimates revealed

that if clouds were suddenly removed and nothing else changed, there would be a

net positive change in the energy balance of the Earth of about 20 Wm-2 . It is

recognized that clouds represent a redistribution of energy between the surface and

the atmosphere that may be larger than the net effect of clouds on the energy balance at the top of the atmosphere. Convection associated with clouds also affects

the exchange of heat between the surface and the atmosphere.

Measurement 1975 1980 1985 1990 1995 2000 2005 2010 2015

Wide FOV

Scanning

TOA

Radiative

Fluxes

N6,7 ERB

ERBE

N6,7 ERB

ERBE

SCARAB

CERES

ERBE*

SRB

SCARAB*

CERES #

ERBE^

CERES#

AIRS/HSB

N7 NCLE

ISCCP

VIRS

MODIS

GLAS

VIRS

MODIS

EOSP

SSM/I

TMI

MIMR

AVHRR

MISR

MODIS

EOSP

SAGE II/III

N7/Sol. Max

ERBE/UARS

ACRIM

??

??

??

Surface

Radiative

Fluxes

Atmosphere

Radiative

Fluxes

Cloud Amount,

Height,

and Optical Depth

Cloud Particle Size/

Phase

Cloud LWP

(ocean)

Aerosol Troposphere

Stratosphere

Solar Constant

* For SW Net and LW Clear-sky only

# Requires cloud properties from coincident cloud imager data: VIRS or MODIS

^ Simulation of CERES analysis using ERBE/AVHRR/HIRS on NOAA 9 spacecraft

Timeline of the primary global

and regional satellite observations for clouds and radiative

properties (Wielicki et al., 1995,

reproduced with permission

from the American Meteorological Society).
Chapter 2 Executive Summary 15

Modeling of the atmosphere including clouds is currently conducted on three

scales: these are global, regional, and cloud-resolving, and the corresponding horizontal resolutions range from 100 km (global), to about 10 km (regional), to about

1 km (cloud resolving). EOS observations will provide data for validation on all of

these horizontal scales, and EOS interdisciplinary investigations will be conducted

at all these scales. The model runs can range from 100-year integrations (global), to

10-day integrations (regional), to 1-day (cloud resolving).

There are many questions regarding cloud characteristics that are faced by

climate modelers. The cloud type that appears to exert the greatest effect on climate

sensitivity in state-of-the-art global general circulation models (GCMs) is the tropical mesoscale anvil cloud that accompanies cumulus convection (Heymsfield and

Donner 1990; Del Genio et al., 1995). The central question is how to represent the

detrainment of ice from cumulus updrafts into anvil clouds. Among many EOS

instruments that will contribute to answering this question are several that will help

define cloud characteristics and, in particular, LIS, whose lightning occurrence record

 TIME SAMPLING MONTHLY NADIR

 (EQ. CROSSING, LT) AVERAGE FIELD OF

 OBSERVATIONS GRID VIEW (KM)

N7 ERB 1979- SW, LW fluxes: 1200 500 km 90; 1000 NSSDC

1990 top of

 atmosphere

N7 New 1979- Cloud amount, 1200 500 km 8; 60 NSSDC

Cloud/ERB 1990 height

HIRS 1989- Cirrus height, 0700, 1400 2.5° 20 NOAA

1993 emittance

ERBE 1984- SW, LW fluxes: 0700, 1400, 2.5° 40; 1000 LaRC V0

1995+ top of Precessing DAAC

 atmosphere,

 cloud forcing

ISCCP 1983- Cloud amount, Every 3 h 280 km 4-8 LaRC V0

1995+ height, optical DAAC

 depth

SRB 1983- SW, LW fluxes: Every 3 h 280 km 4-8 LaRC V0

1995+ surface DAAC

SSM/I 1987- Cloud liquid 0630, 1630 1.0° 32-55 Wetnet

1995+ water path

 (ocean only)

SCARAB 1994- SW, LW fluxes: Precessing 2.5° 80 CNES/

1997+ top of France

 atmosphere

CERES 1997- SW, LW fluxes: Precessing 1.0° 10 LaRC V1

2000 top of DAAC

 atmosphere,

 surface,*

in atmosphere*

VIRS 1997- Cloud amount, Precessing 1.0° 2 LaRC V1

2000 height, optical DAAC

depth, particle

 size/phase

TMI 1997- Cloud liquid Precessing TBD 4.5-37 TBD

2000 water path

 (ocean only)

Pre-EOS PAST AND TIME CLOUD AND DATA

 CURRENT SPAN RADIATION SOURCE

TRMM (45°N-45°S)

Primary global and regional

satellite observations of

clouds and radiation in the

pre-EOS and EOS era. Satellite data with 1/8 to 2-day

coverage, and both day and

night observations (Wielicki et

al., 1995, used with permission

from the American Meteorological Society).
16 EOS SCIENCE PLAN

will serve as an index of convection intensity, and AIRS, whose temperature and

moisture profiles will yield estimates of convective available potential energy.

Many atmospheric circulation systems are organized on the regional or mesoscale (defined as encompassing horizontal length scales of 20-200 km). Mesoscale

convective systems dominate weather over most of the tropics and the summertime

midwestern United States. Mesoscale models (MMs) have become powerful tools

for understanding and forecasting regional atmospheric circulations, taking into

account such features as severe midlatitude cyclones, hurricanes, orographically

forced flow, fronts, and thermally forced flows such as land/sea breezes.

The increased use of MMs has particular promise in the areas of tropical

convection, cirrus cloud evolution, midlatitude cyclonic cloud systems, and prediction of boundary-layer fog and cloud prediction. Several EOS interdisciplinary

investigations are pursuing improved understanding of cloud-climate feedbacks.

The higher spatial resolution, availability of new cloud variables, and greater accuracy of EOS cloud observations will enable better validation of regional cloud

simulations.

Cloud-resolving models are also known as cumulus ensemble models

(CEMs). They include explicit representations of many aspects of cloud microphysics. A typical CEM has a spatial resolution of 1-3 km and variable vertical

resolution of 0.2 to 1 km, with finer resolution in the atmospheric boundary layer

and coarser resolution in the upper troposphere or lower stratosphere above cloud

top.

CEMs include cloud-scale dynamics, subgrid-scale turbulence, and explicit

computation of latent heating. The budgets of all three phases of water are also

explicitly computed. CEMs have been coupled to oceanic mixed-layer models to

elucidate the mechanisms of diurnal variability of clouds and precipitation over the

oceans.

Radiative flux determinations are the highest priority measurements that are

needed to understand the role of cloud feedback mechanisms in the climate system.

At this time net radiative energy flux determinations at the top of the atmosphere

(TOA) need to be supplemented by the more-difficult determinations of the net

radiative energy flux at the Earth’s surface. The vertical distribution of radiative

cooling/heating inside the atmosphere is also very important. In order of priority

are the TOA radiative flux, the surface radiative flux, and the radiative flux at the

tropopause. In order to improve simulations of cloud forcing and its effect on climate sensitivity, more-detailed measurements of cloud properties are needed to

provide understanding and model validation.

TOA radiative flux measurements from space will enter their fourth generation with the CERES instruments on TRMM and on the EOS AM-1 and PM-1

spacecraft. The most recent ERBE measurements provide the standard of comparison for global radiation data sets. The CERES measurement errors are expected to

be a factor of 2-4 lower than the ERBE errors.

Global satellite estimates of radiative fluxes at the surface (up, down, and

net) are now becoming available. There are two independent approaches for determining surface radiative fluxes: 1) Use observed cloud and atmosphere parameters
Chapter 2 Executive Summary 17

with measured TOA broadband fluxes acting as a constraint on the radiative calculations, and 2) Use parameterized relationships between simultaneously observed

TOA fluxes (or radiances) and surface fluxes.

In the EOS time frame calculated shortwave surface flux accuracies should

increase greatly as more-accurate cloud (VIRS, MODIS), atmospheric (AIRS), and

surface (MISR, MODIS) properties become available. Downward longwave fluxes

present a greater problem. In the EOS time frame improved tropospheric water

vapor determinations will help. They will be available from the AIRS/HSB instruments and, over land, from MODIS.

Cloud overlap may be the largest uncertainty for calculations of downward

longwave flux at the surface. In the long term, active systems such as the GLAS

lidar from EOS and a proposed 94-Ghz cloud radar may offer the best solution.

Remotely piloted aircraft will be of great help in testing with-the-atmosphere flux

calculations.

Measurements of cloud properties are very difficult. The EOS MODIS instrument has design capabilities specifically directed toward cloud-property

determinations. Very-high-spatial-resolution measurements from EOS ASTER,

multi-angle EOS MISR data, determinations of the polarization of cloud particles

from EOS EOSP, all will contribute to the validation of the MODIS data. The final

step in cloud remote sensing during the EOS era will be the combination of the

passive sensors just cited with EOS GLAS (the active lidar sensor) and the proposed cloud radar.

Other cloud properties that will be the subject of investigation in the EOS

era include cloud fraction, cloud visible optical depth and thermal infrared emittance, cloud particle size, cloud liquid/ice water path, and cloud mesoscale

organization and structure. Improved spectral resolution (including solar, terrestrial

infrared, and microwave coverage) and spatial resolution, multi-angle coverage,

and the use of both passive and active sensors will lead to various degrees in improvements in the determinations of these cloud properties.

Water Vapor and Climate

Most of the water in the atmosphere is in the form of vapor, and water vapor plays

a critical role in many key processes in the hydrologic and energy cycles. Water

vapor is the most important greenhouse gas, both in terms of its role in maintaining

the current climate and in terms of its role in sensitivity through the water vapor

feedback process. The abundance and vertical distribution of water vapor in the

atmosphere interact very strongly with convection and cloudiness, thereby influencing the albedo of the planet as well as the infrared opacity of the atmosphere.

Data from EOS instruments will improve the quality of global measurements

of the water vapor distribution. In particular, the EOS instruments, AIRS, AMSU,

and HSB, working in combination, will provide more-precise simultaneous measurements of temperature and humidity in the troposphere, with better vertical

resolution than is currently available. Climate feedbacks are sensitive to the vertical distribution of both water vapor and temperature. EOS cloud and moisture

measurements, when combined with wind estimates from data assimilation tech-
18 EOS SCIENCE PLAN

niques and with in situ measurements from field programs, will provide a much

better understanding of the mechanisms whereby the moisture balance of the troposphere is maintained.

Surface temperatures are related to the global distribution of water vapor.

For instance, sea surface temperatures (SST) are highly correlated with the water

vapor over the ocean.

Climate models are only beginning to account explicitly for cloud water and

ice, their transport, and their evaporation to provide a source of water vapor in the

free atmosphere. EOS data will play an important role in validating the new generation of climate models that incorporate these features.

In every respect, the water vapor data sets available to date are inadequate

for climate studies. Radiosondes are limited in their geographic coverage, and satellite retrievals suffer from poor vertical resolution and accuracy. Besides the

improvements in temperature and moisture profiles to be offered by AIRS/AMSU/

HSB, the EOS instruments HIRDLS and MLS will supply improved horizontal and

vertical resolution measurements. Also, the EOS SAGE III instrument will provide

very accurate monitoring of water vapor trends in the stratosphere.

Precipitation

Rainfall plays a central role in governing the climate of the Earth. The latent heat

release in convection is the main source of energy that drives the general circulation of the atmosphere, since much of the solar radiation absorbed by the Earth is

used to evaporate water, which later condenses to release latent heat in the atmosphere during precipitation. Latent heat release in tropical convection forces

atmospheric motions that disperse heat and moisture into the extratropics, diverting

subtropical jetstreams and altering rainfall patterns in midlatitudes.

The distribution of precipitation is highly inhomogeneous in space and time.

Because of the wide range of variability in both time (minutes to years) and space

(less than a kilometer to thousands of kilometers) the long-term accurate mapping

of global precipitation is a daunting task. Atmospheric models have been show to

be able to produce a global precipitation rate to within 10-20% of that observed, but

they have many serious faults otherwise. They differ particularly in their ability to

estimate regional and subcontinental rainfall variability. They also underestimate

the frequency of occurrence of the light-rain category. Because it is impossible to

set up uniform networks of rain gauges over the entire globe, satellite rainfall retrieval algorithms will play a vital role in producing realistic global rainfall

distributions.

As part of the Earth Science Enterprise, The Tropical Rainfall Measuring

Mission (TRMM) launched in November 1997 employs a suite of sensors including one microwave (TMI), one VIS/IR (VIRS), and one active precipitation radar

(PR) with the objective of producing the best rainfall estimates from space, especially for the world’s tropics. Within the EOS measurement system, the key

instruments for precipitation measurement are AMSR-E and HSB on the EOS PM-1

platform.
Chapter 2 Executive Summary 19

Atmospheric Circulation, Hydrologic Processes, and Climate

The presence of clouds, water vapor, and precipitation in the atmosphere significantly alters the Earth’s radiation budget and causes differential heating between

the tropics and the polar regions, between the oceans and the land, and between

clear and cloudy regions. This differential heating is the main driver of the atmospheric large-scale circulation, and the essential component of the circulation is the

wind. The consideration of the atmospheric wind circulation is indispensable in

order to understand the role of the global hydrologic cycle, clouds, water, and precipitation on regional and global climate fluctuations.

It is well recognized that while radiative forcings such as that due to doubling of CO2 may be small, feedback processes in the climate system may amplify

the initial response to the radiative forcing. Especially for climate changes on seasonal and interannual time scales, the large-scale circulation plays a fundamental

role.

The EOS SeaWinds instruments on QuikSCAT and successive Japanese

ADEOS spacecraft will provide surface wind speed and direction over the oceans

from scatterometry, and EOS passive microwave radiometry, using AMSR-E, will

contribute to wind determinations over the ocean as well.

Required Satellite Measurements and Data Sets

Total solar irradiance—By using overlapping flights of the EOS ACRIM instrument, with 0.1% absolute accuracy, it is believed that a relative precision of 0.001%

can be achieved, and that this relative precision would be sufficient to detect climatically significant changes in total solar irradiance on time scales of up to a century.

Radiative fluxes—The expected changes in climate forcing due to solar irradiance changes are about 0.25 Wm-2 , and the expected climate forcing from doubling

CO2 is about 4 Wm-2 . On the other hand variations of radiative fluxes within the

climate system that are associated with season, location, weather, or natural

interannual variability are much larger, often on the order of 100 Wm-2. Current

climate models appear to be in error by tens of Wm-2 so that an achievable accuracy

of 5 Wm-2 is very useful despite being larger than the expected climate forcings.

CERES has been designed to measure the total radiative energy flux, and

MODIS has been designed with both high spectral and spatial resolution in order to

understand what causes changes in radiative flux that may be due to changes in

temperature, clouds, aerosols, water vapor, or other greenhouse gases. Changes in

radiances due to solar and satellite viewing angles need to be taken into account,

and MISR’s ability to view pixels as small as 275 m from 9 angles is an important

contribution. The CERES design also makes angular sampling of radiances possible.

There is an important systematic variability of radiative fluxes on the diurnal

time scale. For this reason CERES is to fly on two sun-synchronous platforms,

EOS AM-1 and EOS PM-1, simultaneously, and, in addition, on the precessing

platform, TRMM. With this scheme there are to be observations of most points on

the Earth at six local times each day.
20 EOS SCIENCE PLAN

With CERES and cloud imagers such as MODIS or VIRS (on TRMM) it

will be possible to provide TOA flux measurements with an estimated absolute

accuracy of 2.5 Wm-2 for longwave and 5 Wm-2 for shortwave radiation. Estimation of surface and internal atmospheric fluxes requires inclusion of temperature,

water vapor, and cloud measurements from the EOS instruments in model calculations. Accuracies to be achieved are less certain than for fluxes at the top of the

atmosphere.

Cloud properties—Cloud properties are derived by many of the EOS instruments:

• MODIS is the prime instrument for EOS cloud property measurements, with

roughly 12 cloud spectral channels and 0.25-1 km fields of view.

• With extremely high spatial resolution, ASTER is used to verify the effects of

sub-pixel cloud variations on MODIS global cloud retrievals. ASTER has eight

cloud spectral channels and 15-90 m spatial resolution for selected 60-km regions.

• MISR has 9 multi-angle view angles functioning in 4 solar spectral channels. It

is used for narrowband cloud anisotropy measurements as well as stereo cloud

heights for broken cloud fields.

• The high spectral resolution of AIRS, with up to 2300 infrared spectral channels, permits measuring the spectral variation of cloud emittances. AIRS

measurements also serve to confirm interpretations of cloud particle phase and

size based on MODIS measurements.

• EOSP is unique in its measurement of reflected solar radiation polarization. Its

measurements are useful at small optical depths and for cloud particle size and

phase estimation. Along with MISR it may provide information on ice crystal

shape.

• GLAS is the active lidar instrument useful for remotely sensing cloud height

and base of optically thin clouds.

• SAGE III and HIRDLS are used for height measurement and detection of extremely thin clouds in the upper troposphere or stratosphere. These are clouds

that might otherwise go undetected.

• CERES data are used to constrain cloud property retrievals and, working with

MODIS or VIRS, to provide radiatively consistent sets of cloud and radiation

data.

• VIRS on TRMM, with 5 spectral channels and a 2-km nadir field of view,

provides an advance over the current AVHRR instrument for cloud measurements.
Chapter 2 Executive Summary 21

The macroscopic properties of clouds that will be determined by the EOS

instruments include cloud fractional area coverage, cloud height, cloud visible optical depth, and infrared emissivity. At the cloud physics level, the EOS instruments

will provide information on cloud particle size and particle phase. It is anticipated

that the effective radius of cloud particles may be obtained with an accuracy of

about 1.25 mm. (This is the accuracy required to give an accuracy in absorbed solar

radiation of 5 Wm-2.)

Lightning flashes—The detection of lightning flashes by LIS on TRMM will

contribute to a global survey of thunderstorm occurrences and cloud electrification

processes.

Atmospheric temperature profiles—The AIRS instrument was designed to

provide a significant benefit to weather forecasting efforts by providing temperature profiles with an accuracy of 1 K for vertical scales on the order of 1 km. The

addition of AMSU microwave channels improves the AIRS capability to provide

accurate temperature profiles under partly cloudy conditions. The addition of HSB

to the AIRS sounding complement improves soundings of both temperature and

humidity in the presence of clouds.

Water vapor—An accuracy of 5-10% for water vapor mixing ratios is required for layers of about equal height at all levels of the atmosphere. The AIRS/

AMSU/HSB instrument complement will provide adequate measurements for the

lower troposphere, and the EOS limb-viewing instruments, SAGE III, HIRDLS,

and MLS, provide good vertical resolution and precision in the upper troposphere

and lower stratosphere.

Precipitation—The primary technology for estimating precipitation globally

during the EOS period will be passive remote sensing from a microwave imager

such as MIMR (for ESA) and AMSR-E for EOS. The obtainable accuracies may be

less than required, but still will represent an improvement over current estimates.

Precipitation estimates for the tropical and subtropical regions will also be available from the passive imager (TMI) and the active precipitation radar (PR), both on

TRMM.

Winds and circulation—Scatterometers, such as the EOS SeaWinds, scheduled to fly on QuikSCAT and on the Japanese ADEOS spacecraft, will be able to

provide surface winds over the oceans with an accuracy of 10% for wind speed and

a 20 ̊ random error. No direct measurements of wind speed are planned for the free

troposphere or the atmospheric boundary layer over land, although it is recognized

that such measurements would be very desirable.

Supporting Surface Observations and Field Experiments

Satellite observations must necessarily be supplemented by field experiments. Many

necessary experiments are incorporated in major field experiments to be enumerated below. These experiments are vital for: 1) assessing the accuracy of

satellite-derived geophysical parameters; 2) evaluating the precision and accuracy

of satellite instrument calibration; and 3) providing enhanced information on the

characteristics of surface and atmospheric constituents assumed in the remote-sensing
22 EOS SCIENCE PLAN

retrievals that are made using satellite observations. Following are a few of the

major field programs that will provide support to the satellite measurements.

FIRE—The First ISCCP Regional Experiment (FIRE) is an ongoing multiagency international program to support the development of improved cloud

radiation parameterization schemes. The program has focused so far on marine

stratocumulus clouds and cirrus clouds. Marine stratocumulus clouds exert a large

influence on the radiation balance of the Earth-atmosphere-ocean system through

their large areal extent, temporal persistence, and high reflectivity to solar radiation. Cirrus clouds exert their greatest radiative influence on the Earth’s climate

through their effects on longwave radiation emitted to space. The intensive field

campaigns that have been conducted as part of FIRE have shown that there are still

discrepancies between remote sensing and in situ estimates of various aspects of

cloud properties.

GEWEX—The Global Energy and Water Cycle Experiment (GEWEX) focuses on observing and modeling the hydrologic cycle and energy fluxes in the

atmosphere, at the land surface, and in the upper layers of the oceans. It has a

validation component that will assist in assessing the accuracy of satellite schemes

for remote sensing of atmospheric temperature and moisture profiles, vertically

integrated water vapor, cloud base altitude, surface longwave flux and cloud optical and microphysical properties.

CLIVAR—The CLIVAR (for climate variability) project is part of the World

Climate Research Program (WCRP) and seeks to understand and predict climate

variability on interannual-to-centennial time scales.

ARM—The Atmospheric Radiation Measurement (ARM) Program is the

largest contribution of the Department of Energy (DOE) to the United States Global Change Research Program (USGCRP). It is a sophisticated measurement

program using ground-based facilities as well as remotely piloted aircraft to characterize the broadband and spectral components of both longwave and shortwave

radiation reaching the Earth’s surface, as well as measure the water vapor, temperature, and wind profiles throughout the lower atmosphere. ARM will have facilities

at three key locales around the world, providing three distinct climatological regimes: 1) the Southern Great Plains of the United States, 2) the western tropical

Pacific, and 3) the north slope of Alaska.

BSRN—The Baseline Surface Radiation Network (BSRN) is an international

program of the World Climate Research Program designed to improve the accuracy

and sampling rate of surface-measured shortwave and especially longwave radiative fluxes. Ultimately, there are to be about 30 sites in the network providing not

only the shortwave and longwave fluxes, but also synoptic and upper air observations as well.

ECLIPS—The Experimental Cloud Lidar Pilot Study (ECLIPS) will obtain

observations of cloud-backscattering profiles from about 10 ground-based lidar

sites around the world. They will provide cloud base altitudes for all cloud types

including cirrus, and, in addition, they will provide cloud top altitudes for optically

thin clouds.
Chapter 2 Executive Summary 23

Interactions with Oceans and Land Processes

Oceans—The storage and transport of heat by the oceans are strongly affected by

surface forcing of momentum, heat, and moisture through interactions with the

atmosphere. EOS scatterometry and passive microwave imaging can give surface

wind stress over the oceans, and this is the key to momentum, heat, and moisture

exchange rates. EOS spaceborne sensors will provide the most viable method of

monitoring the radiative and turbulent heat fluxes at the surface of the oceans, and

these make up the thermal forcing of the oceans.

Adequate resolution of meridional heat transport by the oceans requires an

absolute accuracy of better than 10 Wm-2 in total heat flux, and it is expected that

the EOS sensors will fulfill this requirement.

Monitoring of ocean surface solar irradiance, together with observations of

ocean color by EOS sensors will advance our understanding of the biogeochemical

cycles in the ocean.

Land Processes—Information on all components of the surface radiation

budget is vital for land surface studies, covering the gamut from land surface climatology to ecology. Similarly, information on precipitation and evaporation is needed

for the understanding of the availability of surface moisture for plants, animals, and

people, and knowledge of the large-scale circulations is essential to understanding

the exchange of moisture and gaseous compounds of importance between land areas and the rest of the globe.

Summary of EOS Contributions

EOS will provide an unparalleled opportunity for long-term observation and monitoring of key climate variables such as total solar irradiance; radiative energy fluxes

at the top of the atmosphere, at the surface, and in the atmosphere; cloud properties;

and precipitation. It will also provide improved understanding of the processes that

relate clouds and water vapor to global climate and their effect on climate sensitivity; and also provide more-accurate treatment of clouds and water vapor and their

radiative effects in global climate models. There will be better measurements of

precipitation and consequent improved understanding of the role of precipitation in

connecting atmospheric and surface processes and more-accurate modeling of precipitation in global climate models. Improvements in observational knowledge and

understanding of atmospheric elements and processes will interact very positively

to improve understanding and simulation of land surface and oceanic processes.

The global homogeneous long-term measurements of the climate system to

be provided by EOS will result in enhanced assessment of global change and ultimately result in improved ability to predict seasonal and interannual climate

variability. Through EOS there will be great enhancements in our ability to understand and predict global climate changes and their effects on human activities.
24 EOS SCIENCE PLAN

Chapter 3

Oceanic Circulation, Productivity, and Exchange with the

Atmosphere

Introduction

Chapter 3 focuses on these scientific themes: the interaction between the atmosphere and ocean across the sea surface, including the role of the oceans in the

Earth’s heat and hydrologic cycles; ocean circulation and sea-level change; and the

ocean’s biological system and its interplay with the Earth’s carbon cycle. The chapter reviews the important scientific issues and the observational requirements for

each theme.

The Earth Observing System (EOS) will contribute to all the areas of scientific concern relating to the oceans not only through observations but also through

a number of major interdisciplinary modeling studies making use of the observational data. Crucial to the understanding of ocean dynamics will be worldwide

observations of ocean surface wind stress by the EOS SeaWinds scatterometer instrument, with accuracies of 10-12% in speed. In addition, the EOS AMSR-E passive

microwave instrument will provide complementary continual observations of wind

speeds and stress magnitudes over the oceans.

The role of the oceans in the Earth’s heat and hydrologic cycles will be brought

out in part by surface temperature measurements. The EOS MODIS instrument

will provide sea-surface temperature (SST) measurements, based on infrared emissions from the oceans, for cloud-free conditions to the level of a few tenths of

kelvin. The EOS AMSR-E will provide SST measurements, based on microwave

emissions from the oceans, with an accuracy of 1-1.5 K in all weather conditions.

Several Interdisciplinary Science (IDS) investigations will be dedicated to

studies of ocean circulation and sea-level changes. In addition, the EOS Jason-1

radar altimeter will contribute to the determination of multi-decadal global sealevel variations and their long-term trends; and EOS AMSR-E and SeaWinds

measurements will contribute wind stress information as above.

IDS studies of the ocean’s biological system and its interplay with the Earth’s

carbon cycle will be investigated by several teams which are synthesizing ocean

and atmospheric circulation models. The EOS Moderate-Resolution Imaging

Spectroradiometer (MODIS) instrument and the Earth Science Enterprise instrument, SeaWiFS, will acquire long-term, calibrated satellite data sets of ocean

biogeochemical variables, particularly through those measurements that are called

“ocean color.” Their data will be supplemented by similar measurements made with

the Ocean Color and Temperature Scanner (OCTS), Medium-Resolution Imaging

Spectrometer (MERIS), and Global Imager (GLI) instruments that are provided by

our international partners.
Chapter 3 Executive Summary 25

Background

The oceans play a key role in modulating global climate. About half of the Earth’s

absorbed solar radiation is absorbed by the World Ocean, which is an equal partner

with the atmosphere in moderating the equator-to-pole temperature distribution by

shifting to middle and high latitudes some of the excess heat gained in the tropics.

The ability to forecast well in advance the timing and geographic extent of seasonal-to-interannual climate anomalies is predicated on properly representing the

role of the ocean, which provides the thermal inertia of the climate system because

of its immense and dominant heat capacity.

The oceans also play a key role in moderating the effects of increased carbon

dioxide emissions on global warming. This is because they serve as a “sink” for

much of the carbon dioxide emitted into the atmosphere by both human activities

and natural phenomena. Part of the carbon dioxide taken up by the ocean supports

the growth of the food chain, and part is sequestered in the depths of the ocean.

Major Scientific Questions Related to Ocean-Atmosphere-Surface

Coupling

Three areas of concern related to ocean-atmosphere-surface coupling are momentum exchange, radiative and turbulent thermal fluxes, and freshwater forcing by

evaporation, precipitation, and sea-ice growth and melt.

The exchange of momentum between the atmosphere and the ocean plays a

critical role in climate. Wind stress patterns determine the large-scale upper-ocean

circulation and the major current patterns that transport heat from low to high latitudes and moderate mid- and high-latitude surface temperatures that determine

weather in much of the industrialized world. This stress also determines the strength

of surface mixing and to what extent warm surface water is mixed with cooler

waters from below. It helps determine the shape of the sea surface and local mean

sea level.

The mean thermal fluxes at the ocean surface show a net radiative heating

from the sun balanced mostly by evaporative cooling, that is, by the latent heat of

evaporation. It has been shown that decadal-to-centennial variations in the thermohaline circulation of the ocean depend on exchanges of heat and water with the

atmosphere. Simple atmospheric boundary-layer models can explain much of the

observed pattern of sensible and latent heat fluxes over the global oceans. In the

data-sparse areas of the southern, tropical, and ice-covered oceans, satellite observations will provide the first reliable estimates of the radiative fluxes and, when

combined with boundary-layer models, of turbulent fluxes.

Freshwater forcing is an important aspect of the global water balance. The

ocean loses about ten percent more freshwater through evaporation than it gains

through precipitation. The remaining ten percent is contributed by river runoff. Local

freshwater at the ocean surface limits exchanges of heat and moisture with the

atmosphere. Surface fluxes of heat and moisture drive lower atmospheric vertical

convection, horizontal advection, and precipitation patterns. Notably, surface freshwater forcing is believed to play a primary role in setting the background state and

timing of the El Niño-Southern Oscillation (ENSO) phenomenon. The joint U.S./
26 EOS SCIENCE PLAN

Japan Tropical Rainfall Measuring Mission (TRMM) launched in November 1997

has begun to measure precipitation in the tropics and subtropics.

Major Scientific Questions Related to Ocean Circulation and

Global Sea-Level Rise

Three areas of concern related to ocean circulation are horizontal heat transport,

establishment of surface temperature patterns that control air-sea exchange, and the

transport of nutrients, chemicals, and biota for biochemical processes.

Horizontal heat transport by the oceans is responsible for transporting about

half of the total poleward heat flux in the global climate energy balance.

The poleward transport reaches a maximum in the Horse Latitudes (30-35 ̊

N and S), the area where western boundary currents become well formed. As an

example, the British Isles are kept much warmer than Siberia in winter not by oceanic heat stored locally in the summer, but by the great northward flow of heat in

the Gulf Stream.

Surface temperature patternsthat are important to air-sea exchange are dominated by the need to conserve vorticity and by the mechanisms by which vorticity

is generated and dissipated. Vorticity dynamics determine the position of major

current systems such as the Gulf Stream, the Kuroshio, and the Antarctic circumpolar current and, thus, the related temperature patterns.

Transport of nutrients, chemicals, and biota for biochemical processes controls the productivity of the ocean and its chemical interactions with the atmosphere.

Ocean models that deal with these transport phenomena are just now being developed.

Major climate-related factors that contribute to sea-level rise are thermal

expansion of the oceans as well as ablating mountain glaciers and polar ice sheets.

Major uncertainties exist in the contributions of the Greenland and Antarctic ice

sheets to both recent and predicted future changes in sea level. Even partial shrinkage of the polar ice sheets would inundate the major coastlines of the world and

produce serious economic consequences. At present the combined uncertainties in

the mass balances of land ice are larger than the uncertainty in sea-level rise and

contributions from other sources.

The patterns of ocean circulation are tied to patterns of sea level, but to study

them with altimetric measurements of sea-surface height, the even larger tidal signal from the altimetric observations must be removed. This requires accurate tidal

models which are being improved as part of the oceanographic program within

EOS.

Major Scientific Questions Related to the Marine Biosphere and

the Ocean Carbon System

The enormous oceanic fraction of the planetary surface accounts for the annual

uptake of about 40% of the carbon dioxide emissions of mankind. The exchange of

gases, and in particular carbon dioxide, between air and sea is a crucial part of the
Chapter 3 Executive Summary 27

climate perturbation equation and as such is a critical

area of research for the EOS program. Among questions that need to be resolved are these:

• How do changes in surface forcing of heat, momentum, and nutrient fluxes affect carbon cycling in the

upper oceans?

• What are the amounts of the fluxes of carbon dioxide, carbon monoxide, and dimethyl sulfide across

the air-sea interface?

• What are the factors affecting the productivity of the

oceans?

Global estimates of the mean and time-varying

components of ocean photosynthetic carbon production

and its relation to nutrient cycles differ widely and will

not be resolved without sophisticated analyses and models involving both satellite and in situ data. Large

uncertainties exist in the estimates of the carbon dioxide flux across the ocean-atmosphere interface. The

estimates are based on the gas-exchange flux equation,

which uses an empirical proportionality parameter that

suffers from considerable uncertainty. Rivers move carbon, nutrients, sediments, and freshwater to the ocean,

and human activities are directly and indirectly affecting these river sources in ways that must be quantified

on a global scale.

The EOS MODIS instrument will be key to the detection of the sunlightstimulated chlorophyll a fluorescence signal in coastal waters, which serves as a

good proxy for phytoplankton biomass and such constituents as the concentration

of marine detritus.

EOS Plans for Modeling and Observations of the Oceans

EOS interdisciplinary science investigations already well underway are using the

existing knowledge base of oceanic observations to improve our knowledge of the

behavior of the world oceans. These investigations will move to a new level with

the advent of the improved EOS observations that will become available starting

with the launch of the first EOS satellite, EOS AM-1, in 1999. The space-based

observations will be augmented by many worldwide field programs as well, conducted by U.S. and international science teams. pW

Latitude

6

4

2

0

-2

-4

-6

-90 -75 -60 -45 -30 -15 0 15 30 45 60 75 90

Total Transport

Atmosphere Transport

Ocean Transport

A

-40 -30 -20 -10 0 10 20 30 40 50 60 70

Indian

All Oceans

Atlantic

Pacific

2

1

0

-1

-2

Latitude

pW

B

A) Estimates of the annual mean

meridional energy transport (positive northward) required by the

energy balance at the top of the

atmosphere, estimated from atmospheric observations by Peixoto

and Oort (1984) and the Earth Radiation Budget Experiment, in

petawatts (=1015 W). The oceanic

transport is obtained by subtracting the atmospheric energy

transport from the total transport

required by the annual energy balance.

B) Meridional profiles of the northward oceanic heat transport for

the various oceans, computed indirectly from the surface heat

balance (Adapted from Hsiung,

1985).
28 EOS SCIENCE PLAN

Chapter 4

Greenhouse Gases and Atmospheric Chemistry

Introduction

Chapter 4 focuses on processes that lead to changes in the atmospheric burden of

greenhouse gases and, potentially, to global climate change. These processes can

be characterized as “biogeochemical” in that they involve the interaction of biological, geochemical, and photochemical processes. Thus, the questions of particular

concern have to do with those processes that affect the global carbon dioxide, carbon monoxide, methane, nitrous oxide, and ozone budgets. In this chapter, six science

questions are addressed; relevant EOS data products and synthetic analyses are

presented; EOS algorithms, observations, and required additional data are reviewed;

and the status and needs of synthesis and integrative modeling are described.

The Six Science Questions

The six questions have to do with: 1) the effect of changing land cover/land use on

fluxes of greenhouse gases; 2) the effect of interannual variability in climate on

biogeochemistry; 3) the effect of changing global hydrology and patterns of soil

moisture on fluxes of methane and carbon dioxide in wetlands; 4) the spatial distribution and budget of tropospheric ozone; 5) the vertical distribution of tropospheric

ozone; and 6) the processes that interact to control ocean carbon uptake.

Changes of land cover/land use constitute one of the most potent forces affecting global greenhouse gases. Whereas fossil fuel burning and cement production

add 5.5 Gt C/yr to the atmosphere, land-cover change adds another 1-2 Gt C/yr.

Land-cover changes also affect nitrous oxide and nitric oxide emissions.

Interannual variability in climate has been shown to lead to substantial

interannual variability in terrestrial ecology and atmospheric chemistry. Remote

sensing from satellites is the best means for understanding the geographic distribution of climate anomalies and the spatial response of the oceans and land ecosystems.

Changes in global hydrology and patterns of soil moisture in wetlands strongly

affect the methane budget. New improved regional and global data sets on wetland

extent and seasonality are needed.

The spatial distribution and budget of tropospheric ozone are caused by changing sources of precursors arising from fossil fuel burning, biomass burning, and,

possibly, changing biogenic sources in soils and vegetation.

The vertical distribution of tropospheric ozone influences the integrated radiative effect of ozone, and, hence, its effects on climate. The vertical profile will

change as the geography of sources changes, as atmospheric convection and mixing change, and as further anthropogenic sources are introduced. Accurate predictive

models will be extremely difficult to develop and evaluate without strong constraints from global observations.
Chapter 4 Executive Summary 29

The processes that interact to control ocean carbon uptake are physical, chemical, and biological. The kinetics of carbon dioxide gas transfer across the

ocean-atmosphere interface is slow, on the order of a year, much slower than biological processes leading to carbon uptake. What determines the partitioning of

anthropogenic carbon dioxide among the atmosphere, the oceans, and the terrestrial biosphere is still the subject of research.

EOS Data Products and Analyses

Specific EOS scientific activities that relate to greenhouse gases and atmospheric

chemistry can be described in terms of their contributions to the understanding of

the carbon cycle, methane production and abundance, nitrous and nitric oxide production and abundance, and atmospheric chemistry and ozone.

EOS products will encompass many aspects of the carbon cycle. A global

database of high-resolution analyses of land-cover change will be developed. Estimates will be made of the contribution of biomass burning to atmospheric CO2.

Trends in carbon fixation by terrestrial vegetation will be monitored in terms of

changes in leaf-area index and fraction of photosynthetically-active radiation that

is absorbed by vegetation. Related data of various types will be integrated into

global synthetic analyses via atmospheric transport models.

Key EOS products related to methane include wetland hydrology (extent

and duration of inundation) and land cover and productivity in methanogenic regions and in areas of methane oxidation.

Measurements related to nitrous and nitric oxide production and abundance

will be provided by the EOS Tropospheric Emission Spectrometer (TES) instrument.

Ozone and related species will be monitored by EOS instruments, particularly those on the Chemistry 1 mission. Several instruments will measure ozone

distribution directly. Measurements of Pollution in the Troposphere (MOPITT) will

make measurements of carbon monoxide and methane. Moderate-Resolution Imaging Spectroradiometer (MODIS) observations of fire will lead to estimates of

biomass burning contributions of hydrocarbons, methane, oxides of nitrogen, and

nonmethane hydrocarbons to ozone production.

Figure A shows how EOS data and models can be integrated to model the

carbon cycle. The ocean, ecosystem, and land-use-change fluxes are combined to

produce spatial maps of terrestrial sources and sinks of CO2, with fossil and cement

sources also included from statistical data.

Figure B shows how trace gases and the ozone cycle may be modeled. Fluxes

of nitrogen- and carbon-based gases are derived from surface observations and then

used as inputs to atmospheric chemical transport models. Direct retrievals of the

distributions of greenhouse gases from TES, MOPITT, and High-Resolution Dynamics Limb Sounder (HIRDLS) and other EOS instruments can also be passed to

the chemical transport models. Other information about anthropogenic gases from

various sectors of the economies of the world can also be passed to the chemical

transport models.
30 EOS SCIENCE PLAN

EOS Models

A

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m

o

s

p

h

e

r

i

c

C

O

2

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n

c

&

T

r

a

n

s

p

o

r

t

Industrial

Transportation

Energy

Chemicals

Terrestrial Hydrology

∆ snow

∆ ET

∆ soil water

Marine

 ∆ pCO2

 ∆ NPP

 ∆ CO2 exchange

Terrestrial

 ∆ NPP

 ∆ carbon storage

Physical Atmosphere

precip

temp

radiation

humidity

4DDA

Oceans

 ocean color

 wind stress

 SST

Hydrology

 soil wetness

 inundation

 snow

Terrestrial Processes

LAI/FIPAR

NPP

Biomass

amounts

Land Use/

Land Cover

wind

CARBON CYCLE CARBON CYCLE

Atmospheric Dynamics

& Transport

Figure A
Chapter 4 Executive Summary 31

EOS Data EOS Models

Physical Atmosphere

4DDA

surface T

etc.

Atmospheric Chemistry

& Transport

transport

radiative forcing

Chemical Atmosphere

Hydrology

inundation

surface

wetness

snow

retrievals

Industrial

Transportation Energy

Chemicals

Terrestrial

 FIPAR, LAI, NNP

Terrestrial N Cycle

Trace Gas Sources/Sinks

∆CH4, ∆NMHCs,

∆CO,∆NO, ∆N2O

Emission Factors

Land Cover

land cover change,

biomass burning

TRACE GASES TRACE GASES

Figure B
32 EOS SCIENCE PLAN

Chapter 5

Land Ecosystems and Hydrology

Introduction

Chapter 5 focuses on the role of the land system in the three areas of land-climate,

land-hydrology, and land-vegetation interactions. Fluxes of CO2 and other greenhouse gases from the land surface influence the global circulation directly. Changes

in land cover lead to changes in the land-surface biophysical properties of energy

and mass exchange and also affect surface hydrologic balances. Finally, both climate and hydrology changes jointly control biospheric productivity, the source of

food, fuel, and fiber for humankind. The EOS program provides satellite-based

remote-sensing instruments that can quantify the spatial and temporal variability of

the land-surface attributes that are critical to understanding these complex interactions.

The primary concern regarding land-climate interactions is to learn how

changes in land-surface processes and properties interact with, and cause changes

in, both regional and global climate. Land-surface properties such as type of cover,

leaf-area index, roughness length, and albedo must be determined and made available to land surface parameterization (LSP) schemes, which are then coupled to

Atmospheric General Circulation Models (AGCMs). These models are then used

interactively to predict climate change and also changes in land-surface properties

such as characteristics of vegetation that are related to climate change.

The primary concern regarding land-hydrology interactions is with changing climate and land-surface characteristics that may combine to change precipitation

patterns, surface-water partitioning and storage, and river flows. Of further concern

is the land processes that may alter water quality: erosion, sedimentation, and river

biogeochemistry.

The primary concern regarding land-vegetation interactions is with how biome

distribution is influenced by, and in turn influences, changes in land cover and

climate. There are serious questions relating to how the regional distribution and

magnitude of crop, range, and forest productivity will change with climate and

land-use change.

Major land-surface science issues can be treated in terms of the three aspects

of land-climate, land-hydrology, and land vegetation.

Land-Climate Science Issues

Many land-climate science issues are addressed in this chapter of the EOS Science

Plan. The current generation of AGCMs that is being used to study climate contains

representations of land and ocean surface interactions with the atmosphere. A new

generation of land-surface models (LSMs) has been developed to work with the
Chapter 5 Executive Summary 33

AGCMs. The LSMs generally contain formulations that model surface radiation

fluxes, turbulent and mass fluxes, liquid water fluxes, and control of water vapor

and CO2 fluxes by vegetation. Various LSMs still exhibit major differences in their

predictions of change. Current models still do not do a good job of representing

water and energy exchanges between the land and the atmosphere that must be

known in order to predict correctly the temporal and spatial fields of precipitation

and surface radiation.

There are questions regarding possible highly complicated interactions and

feedbacks between the atmosphere and the surface wherein elevated levels of atmospheric CO2 may cause changes in the biosphere. It has been found that realistic

representations of land-surface cover and moisture characteristics are likely to lead

to greatly improved weather forecasting skill.

Land-Hydrology Science Issues

Many land-hydrology phenomena must be addressed at smaller scales than are commonly employed in general circulation models (GCMs) and other climate modeling

representations. The challenge to EOS scientists is to strive to improve hydrologic

understanding at these critical human scales. Thus key science issues for land-hydrology are: 1) to identify and quantify key hydrologic variables across a range of

scales and 2) to develop or modify hydrologic process models to take advantage of

operational and realistic data sources.

The extensive list of hydrologic variables that require more study includes

precipitation, runoff, evapotranspiration, near-surface soil moisture, infiltration and

deep percolation, radiation, and near-surface meteorology. Information is also needed

for the estimation of the land-surface water balance and the estimation of the possibilities for extreme hydrologic events such as severe storms, floods, and droughts.

The role of river biogeochemistry in affecting water quality and the functioning of

aquatic ecosystems must also be examined.

Vegetation Science Issues

EOS vegetation science issues encompass regional-to-global scales, from the carbon balance of the boreal forest to biospheric net primary production. Because of

the short time scale of vegetation responses to climate, EOS measurements will

range from following interannual variability in spring phenology to seasonal changes

in daily terrestrial surface CO2 balance to annual and interannual changes in net

primary production (NPP).

Direct measurements from EOS will include aspects of land cover and landcover change. Other biophysical variables such as leaf-area index, fraction of

photosynthetically-active radiation that is absorbed, albedo, and vegetation indices

are derived from direct measurements. A key derived product is NPP, and the EOS

Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument was specifically designed, in part, to calculate this parameter. MODIS will produce values

of NPP on a weekly basis to be available globally at 1-km resolution.
34 EOS SCIENCE PLAN

Related EOS Science Measurements

Among the suite of EOS instruments to be flown starting in 1998, four instruments will be playing key roles

in providing data about the Earth’s surface characteristics. These instruments are the Advanced

Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Enhanced Thematic Mapper +

(ETM+), Multi-Angle Imaging Spectroradiometer

(MISR), and MODIS.

ASTER, operating in the visible, shortwave infrared, and thermal infrared, will provide surface

reflectances and radiative (brightness) temperatures

with 15-to-30-m resolution. The thermal infrared radiances can be used to derive

surface kinetic temperatures and spectral emissivities. The kinetic temperatures can

then be used to determine sensible and latent heat fluxes and ground heat conduction. Still other parameters can be derived from the surface kinetic temperatures as

well.

ETM+ on the Landsat-7 platform, operating in the visible, near and shortwave infrared, and thermal infrared, will be used primarily to characterize and

monitor changes in land cover and land-surface processes. It will have a panchromatic band with 15-m resolution, and will have 30-m resolution in the visible and

infrared channels, except for 60-m resolution in the thermal infrared. The characteristics of ETM+ are such that it will provide data sufficiently consistent with

previous Landsat data to meet requirements for global-change research.

MISR, operating in the visible, and viewing the Earth at nine discrete angles,

will provide measurements that lead to determination of surface albedo and vegetation canopy structural parameters, thereby leading to derivations of

photosynthetically-active radiation and improved values of canopy photosynthesis

and transpiration rates.

MODIS, operating in the visible and infrared with spatial resolution from

250 m to 1 km at nadir, will be the primary sensor for providing data on terrestrial

biospheric dynamics and vegetation process activity. Land products from MODIS

include spectral albedo, land cover, spectral vegetation indices, snow and ice cover,

and surface temperature and fire, plus biophysical variables such as leaf-area index

and fractional photosynthetically-active radiation.

Human-induced changes in global land cover estimated by comparing AVHRR NDVI data, expressed as leaf-area index, with

potential leaf index computed

from long-term climatological

data and hydrologic-vegetation

equilibrium theory (Nemani et al.,

1996).
Chapter 6 Executive Summary 35

Chapter 6

Cryospheric Systems

Introduction

Chapter 6 focuses on those portions of the Earth’s surface where water is in a solid

form and includes all these elements: sea ice, lake ice, river ice, snow cover, glaciers, ice caps and ice sheets, and frozen ground (which includes permafrost). As an

integral part of the global climate system the cryosphere has important linkages and

feedbacks with the other elements of the system such as surface energy and moisture fluxes, clouds, precipitation, hydrology, and atmospheric and oceanic circulation.

Knowledge of the many elements of the cryosphere is essential to the correct modeling of climate and predictions of global change.

At a time of general concern with the possibility of human-induced global

warming there is a particular concern with the possibility of associated melting ice

sheets and the consequent rise in sea level that may ensue. In addition to the possible flooding of coastal areas and low-level oceanic islands due to sea-level rise,

there is also the possibility of adverse effects on water supply and navigability of

waterways. Accurate information on the rate and magnitude of changes in the

cryospheric elements is essential for policy and decision making, particularly over

the high latitudes of the Northern Hemisphere, where climate warming is projected

to be the greatest.

The importance of the cryosphere in climate studies is clearly reflected in

the Earth Observing System (EOS) program. EOS now incorporates a dedicated

snow-and-ice Distributed Active Archive Center (DAAC), a specific satellite mission (Ice, Clouds, and Land Elevation Satellite [ICESat]) dedicated to ice-sheet

altimetry, and a considerable number of interdisciplinary science investigations (IDS)

undertaking research to improve understanding and modeling of cryospheric processes, cryospheric variability, and cryosphere-climate interactions. In addition to

the altimetry measurements to be provided by the Geoscience Laser Altimeter System (GLAS) on the ICESat spacecraft, other EOS instruments such as the

Moderate-Resolution Imaging Spectroradiometer (MODIS) and Advanced

Spaceborne Thermal Emission and Reflection Radiometer (ASTER), operating in

the visible- and infrared-wavelength regions will be providing surface temperature

and reflectivity measurements and snow-cover distribution, and the Advanced Microwave Scanning Radiometer-EOS Version (AMSR-E) instrument, operating in

the microwave region, will make complementary determinations of snow cover

and sea-ice characteristics and distribution.
36 EOS SCIENCE PLAN

Background

The majority of the world’s ice volume is in Antarctica, principally in the East

Antarctic Ice Sheet, but winter snow and ice in the Northern Hemisphere have the

largest area. The most important physical properties of snow and ice that modulate

energy exchanges between the surface and the atmosphere are surface reflectance,

thermal diffusivity, and latent heat. Thermal diffusivity is a measure of the ability to

transfer heat, and latent heat is a measure of the ability to change state. Surface

roughness, emissivity, and dielectric characteristics contribute importantly to making observations of snow and ice from space.

Snow cover has the largest areal extent of any component of the cryosphere,

with a mean maximum areal extent of approximately 47 million km2, most of it

located in the Northern Hemisphere. A close relationship between hemispheric air

temperature and snow cover has been observed during the satellite-observation years.

This has led to considerable interest in monitoring Northern Hemisphere snowcover extent for detecting and monitoring climate change. Interestingly, the control

of shortwave energy exchange by snow cover affects the availability of photosynthetically-active radiation (PAR) needed for the productivity of sub-ice algae.

Sea ice covers much of the polar oceans, and satellite data have shown considerable seasonal, regional, and interannual variability in the sea-ice covers of

both hemispheres. The passive microwave record from late October 1978 through

the end of 1996 shows that the extent of Arctic sea ice has been decreasing at a rate

of 2.9% per decade, while the extent of Antarctic sea ice increased by 1.3% per

decade. Both “leads” and polynyas are very important components of the sea-ice

regime, playing a dominant role in exchanges of heat and moisture to the atmosphere during the polar winter. Polynyas also have an important role in primary

productivity, allowing significant absorption of PAR within the water column.

Lake ice and river ice evince considerable variability in their dates of appearance and disappearance. The sizes of the ice bodies are too small to exert other

than localized climatic effects. Still, observations of lake ice can serve as a useful

proxy climate record. River-ice observations are less useful as a climatic proxy

record because river-ice formation is strongly dependent on a river-flow regime

that is affected by many other factors. Accordingly, there is no river-ice research

component in EOS. The appearance and disappearance of lake ice are readily observed in the visible, and microwave sensors are well suited to monitoring important

lake-ice characteristics such as freeze-up, break-up, freeze-to-bottom, and surfacemelt onset. Freeze-up and break-up correlate well with air temperature or

freezing-degree days.

Permafrost is perennially frozen ground and may occur where mean annual

air temperatures are less than -1 or -2 ̊ C. It underlies approximately 20% of Northern

Hemisphere land areas, with thicknesses exceeding 600 m along the Arctic coast of

northeastern Siberia and Alaska. Permafrost may form under present-day polar climates where glaciers retreat or land emergence exposes unfrozen ground.

Ice sheets are the greatest potential source of global freshwater, holding approximately 77% of the global total. This corresponds to 80 m of world sea-level

equivalent, with Antarctica accounting for 90% of this and Greenland accounting
Chapter 6 Executive Summary 37

for most of the remaining 10%. Climatic perturbations produce only slow variations in ice sheets, occurring over glacial and interglacial periods. Valley glaciers,

on the other hand, respond rapidly to climatic fluctuations, with typical response

times of 10-50 years. While glacier variations are likely to have minimal effects on

global climate, their recession may have contributed one third, to one half of the

observed 20th-century rise in sea level. The mass balance of land-based glaciers

and ice sheets is determined by the accumulation of snow, mostly in winter, and

warm-season ablation due primarily to net radiation and turbulent heat fluxes to

melting ice and snow from warm-air advection. Satellites are playing an increasingly important role in furthering understanding of the Greenland ice-sheet mass

balance by providing accurate surface-elevation data, ice-flow velocity, and surface ablation information.

Major Scientific Questions Related to Cryospheric Science

Three areas of concern related to cryospheric science are: 1) representation of

cryospheric processes in climate and hydrological models; 2) cryosphere-climate

linkages and feedbacks; and 3) cryospheric variability and change.

Representation of Cryospheric Processes in Climate and

Hydrological Models

Recent studies have shown that atmospheric general climate models (GCMs) suffer

from inadequate treatment of sea-ice processes involving snow albedo, heat storage, and conduction. Lack of vegetative masking of snow albedo in some models

has led to a significant cold bias in spring air temperatures over northern Eurasia.

Year-round calculations of snow cover have a strong effect on the calculations of

runoff. All of the following processes must be properly represented in models in

order to provide realistic simulations of the snowpack: snow metamorphism (or

aging), resolution of vertical gradients, and snow-rain separation. There is a general lack of suitable evaluation data to assess the performance of snowpack models.

EOS products from MODIS, such as surface temperature, albedo, and snow cover

and EOS products from AMSR-E, such as snow-water equivalent and depth, will

be of great assistance here. While there is as yet no widely suitable method to directly map snow-cover equivalence in rugged mountains, higher resolution snow

products from EOS will help to address this issue. There is still the need for multipolarized synthetic aperture radar (SAR) to make reliable estimates of snow-water

equivalence in alpine areas.

Sea-ice dynamics—advection and deformation—must be included in climate models to account for the freshwater provided by melting sea ice advected

from the Arctic into the Greenland and Norwegian Seas and to reproduce dynamic/

thermodynamic feedback effects involving open-water “leads”. Also, sea-ice changes

have a major impact on the availability of moisture and the mass balance of major

ice sheets, especially Antarctica. Recent studies have shown that relatively modest

changes in thermodynamic parameterizations of sea ice may have a disproportionate effect on simulated ice-thickness variability and thereby have a major impact on

simulated climate variability.
38 EOS SCIENCE PLAN

Lake-ice neglect in GCMs has led to incorrect simulation of the seasonal

cycle of discharge from the Mackenzie River and to an incorrect supply of freshwater to the Arctic Ocean in coupled models.

Permafrost restricts moisture exchanges between surface water and deep

ground water and is therefore an important factor in controlling drainage and the

areal and spatial distribution of wetlands. Accurate simulation of permafrost processes such as active-layer development will require modeling schemes with

additional soil layers and better understanding of heat and water flow in organic

soils. The inclusion of frozen soil in hydrological models is a major objective of the

Canadian Global Energy and Water Cycle Experiment (GEWEX) program.

Glaciers and ice sheets need improved representation in climate models and

in hydrological models as well. There are major uncertainties regarding the future

behavior of the great ice sheets, and there are major knowledge gaps that need to be

filled in order for climate models to provide better estimates of glacier and icesheet mass balance and their contributions to sea-level change. Among the knowledge

gaps are the linkage of meteorology to mass balance and dynamic response, the

need for research on a broader spectrum of glacier environments, quantification of

the process of meltwater refreezing, and increased understanding of the process of

iceberg calving.

Runoff is one of the major links between glaciers and ice sheets and the

global climate system, and runoff is crucially important from a water-resources

perspective. Glacier and ice-sheet runoff are also important from an ecological perspective, affecting habitat sustainability and wildlife management through influences

on stream-water turbidity and temperature.

Representation of Cryosphere-Climate Linkages and Feedbacks

Cryosphere-climate feedbacks can be classified into the main categories of feedbacks working through the freshwater cycle and feedbacks working through the

surface-energy balance. The freshwater cycle is intimately connected to the

cryosphere through the storage and transport of freshwater in solid form. The storage and transport occur over a wide range of time scales and, therefore, are involved

in climate variability over a similar range of time scales. On short time scales (seasonal and annual) the accumulation and melting of snow dominates the hydrological

cycle of many alpine and high-latitude drainage basins. On annual-to-decadal time

scales sea ice can store freshwater and transport it from one region to another, as ice

drifts under the influence of winds and currents. In the Northern Hemisphere ice

melts as it is transported out of the Arctic into the North Atlantic, thus forming a

stabilizing freshwater layer at the surface. The freshwater layer may moderate deep

convection in the North Atlantic and thereby affect the global “conveyor belt” circulation, which is important for transporting oceanic heat northward and sequestering

carbon dioxide in the deep ocean. On still-longer time scales, melting of large glaciers and ice sheets can lead to substantial raising of global sea level.

The surface-energy balance over both land and ocean can be modified as a

result of the cryosphere’s interaction with the climate system. The two principal
Chapter 6 Executive Summary 39

mechanisms involving ice and snow cover are insulation of land and ocean surfaces

from the atmosphere, or feedback with outgoing longwave radiation (OLR), and

enhancement of the surface albedo, or shortwave feedback. The shortwave feedback is the classic feedback between temperature and albedo wherein higher air

temperatures melt ice and snow and thereby decrease albedo, leading to greater

absorbed energy and warmer temperatures.

Sea-ice % 7% daily 20 km — AMSR-E

concentration

Floe-size — 10% weekly 100 km — MODIS,

statistics Radarsat

Ridge statistics — 10% weekly 100 km — Radarsat

Cloud fraction — 4% / 30% daily 1 km — MODIS,

climatology,

stations

Cloud optical — 15% daily 1 km — MODIS,

depth aircraft

Cloud particle — — daily 1 km — MODIS,

phase aircraft

Cloud effective — 25% daily 1 km — MODIS,

particle radius aircraft

Cloud top — 6% daily 1 km, 100 km — AIRS,

temperature AMSU,

MODIS

Cloud top — 6% daily 100 km — AIRS,

pressure AMSU,

HSB

Atmos. ice — — — — — ICESat,

crystal precip. aircraft

Atmospheric — — — — — ICESat,

aerosol aircraft

Surface albedo — 0.05 / 0.1 daily 1km — MODIS,

climatology

Ice surface — 1 K / 2 K daily 1 km, 100 km — MODIS,

AIRS,

buoys,

stations

Surface — — — — — laser,

roughness survey

Humidity g/kg 10% 2/day (d, n) 50 × 50 2 km::Atmos AIRS (05),

profile (goal)::5% km::G HSB

Temperature K 1.0 K::0.4 K 2/day (d, n) 50 × 50 2 km::Atmos AIRS (07)

profile km::G

Data sets required to develop

and validate parameterizations

of the surface-energy-exchange process (WCRP, 1997).

 PARAMETER UNITS ACCURACY TEMPORAL SPATIAL VERTICAL SOURCE

 NAME NEED/AVAIL RESOLUTION RESOLUTION RESOLUTION

OR ABSOLUTE::REL OR HORIZONTAL

RESOLUTION::COVER
40 EOS SCIENCE PLAN

Representation of Cryospheric Variability and Change

To be adequate, a good representation of cryospheric variability and change must

account for variability in snow, sea ice, lake ice, frozen ground and permafrost, and

glaciers and ice sheets.

The existing satellite snow databases are currently too short to provide information on the natural variability in continental-scale snow cover needed for

climate-change detection and for validating transient simulations used in global

climate models. Still, two important databases are available for assistance with this

problem. The weekly National Oceanic and Atmospheric Administration (NOAA)

visible satellite-based snow-cover analysis dates back to 1972, and there are Scanning Multispectral Microwave Radiometer (SMMR) and Special Sensor Microwave/

Imager (SSM/I) passive microwave data from 1978, which can be used to derive

snow extent, snow depth, and snow-water equivalence. It is interesting that the

rapid decrease in Northern Hemisphere spring snow-covered area that characterized the 1980s appears to have reversed itself during the 1990s.

Determining the mass or volume of sea ice requires measurements of both

areal coverage and thickness. The AMSR-E will be the EOS instrument that will

continue the satellite record of sea-ice concentration and extent, but so far there is

no direct satellite method to measure ice thickness. (A system is being developed to

use SAR along with kinematic histories of sea ice to derive ice thickness.)

Ice surface m 0.5 - 5 m yearly 10 - 100 m 1 - 10 m ICESat, SAR

topography /?

Area covered km2 0.01 - 0.5 km-2 yearly 100 m - 1 km — ASTER, AVHRR,

by ice /0.001 km-2 ETM, MODIS, TM

Ice-thickness m 0.5 - 5 m yearly 100 m - 1 km 1 - 10 m SAR

distribution /?

Ice-flow m d-1 0.05 - 0.5 m d-1 daily, yearly 0.1 - 1 m — ICESat, SAR

velocity /?

Seasonal ice/ km2 0.01 - 0.5 km-2 daily, yearly 10 m - 1 km — ASTER, AVHRR,

snow cover /0.001 km-2 ETM, MODIS, TM

Snow-depth m - 0.25 m daily, yearly 10 m - 1 km 0.05 - 0.5 m ASTER, SSM/I

distribution

Snow-water mm 2.5 - 25 mm daily 10 m 5 - 50 mm SAR

equivalent

Surface K 0.5 K / 2 K daily 10 m - 1 km — ASTER, AVHRR,

temperature ETM, MODIS, TM

Albedo % 1% daily 10 m - 1 km — ASTER, AVHRR,

distribution /5-10% ETM, MODIS, TM,

cloud cover % 10% daily 1 - 10 km — CERES

Meltwater Yes — daily 1 - 100 m — ASTER, TM, ETM

runoff /No /—

Data sets and accuracy required to monitor glacier and

ice-sheet responses to

changing climate (WCRP,

1997).

PARAMETER UNITS ACCURACY TEMPORAL SPATIAL VERTICAL SOURCE

NAME NEEDED/AVAILABLE RESOLUTION RESOLUTION RESOLUTION
Chapter 6 Executive Summary 41

Satellite observations of lake-ice freeze-up/break-up are particularly valuable for validating/calibrating physical lake-ice models. Satellites operating in the

visible and both passive and active microwave regions can all provide useful information.

Satellites, through their global coverage, are ideally suited for monitoring

the vast, uninhabited areas underlain by permafrost. Unfortunately, permafrost being a sub-surface feature, cannot be observed directly from space so that extent and

change have had to be indirectly deduced from related micro-climate and surface

vegetation characteristics that can be detected by remote-sensing techniques. Recent work has shown that it is possible to use multidimensional SAR configurations

together with optical sensors to map frozen ground and associated features.

EOS promises to make great advances in determining glacier and ice-sheet

responses to climate change. Surface-area determinations and differentiation into

cover classes have been achieved using Thematic Mapper (TM) and Advanced Very

High-Resolution Radiometer (AVHRR) data for the Greenland ice sheet. SAR data

may be useful for the determination of the ice-thickness distribution, and data from

SAR and GLAS may help to determine small changes in surface elevations.

Required Measurements, Data Sets, and Parameterizations

The table on page 39 (for parameterizations of the surface-energy-exchange process) is presented here as an example of the measurements that will be made by

elements of EOS. This example shows the use of the AIRS/AMSU/HSB, AMSR-E,

GLAS, and MODIS instruments along with instrumented aircraft, buoys, and ocean

stations.

As another example, the table on page 34 shows the roles of ASTER, AVHRR,

CERES, ETM, GLAS, MODIS, SAR, SSM/I, and TM (on Landsat) in contributing

to monitoring glacier and ice-sheet responses to changing climate.
42 EOS SCIENCE PLAN

Chapter 7

Ozone and Stratospheric Chemistry

Introduction

Chapter 7 focuses on stratospheric ozone, its role in climate change, and the natural

and anthropogenic causes of changes in it. Stratospheric ozone shields the Earth’s

surface from solar ultraviolet radiation. Stratospheric ozone also plays an essential

role in setting the temperature structure and therefore the radiative heating/cooling

balance in the atmosphere, especially in the stratosphere.

Four major sections of the chapter give: first, a general background of what

is known about stratospheric ozone, second, a review of major scientific issues,

third, a description of required measurements and data sets, and fourth, the anticipated EOS contribution to the fund of knowledge and understanding of stratospheric

ozone.

Background Information

Ozone changes can affect climate, in the sense that removal of ozone from the

stratosphere would cause cooling of the stratosphere and beyond that a small, but

non-negligible, offset to the greenhouse forcing from CO2, N2O, CH4, CFCs, etc.

The size of the radiative forcing due to stratospheric ozone loss is very sensitive to

the profile shape assumed for that loss.

What might be called normal ozone changes have been observed on various

time scales, including seasonal and interannual. Seasonal changes are basically determined by the winter-summer changes in the stratospheric circulation. Interseasonal

changes are linked to the eleven-year solar cycle in UV input from the sun and to

the amount of volcanic aerosols in the stratosphere. Superimposed on the natural

changes are anthropogenic changes largely related to the release into the atmosphere of human-made chemicals containing chlorine.

The most significant departure from the natural ozone distribution has been

the change in Antarctic polar ozone, leading to the phenomenon known as the ozone

hole. Not until 1996 have changes in Arctic polar ozone been detected that are in

any way comparable to the changes in the Antarctic polar ozone. In recent decades

it has become clear that there are also small but statistically significant decreases in

midlatitude stratospheric ozone as well.

Changes in stratospheric ozone distribution can be understood in terms of

chemical processes, transport, interactions with aerosols and polar stratospheric

clouds, and interactions with solar ultraviolet radiation and energetic particles.

The basic outline of the chemical processes that control stratospheric ozone

appears to have been established. Principal ozone destruction processes have to do

with catalytic reactions involving hydrogen, nitrogen, chlorine, and bromine radi-
Chapter 7 Executive Summary 43

cals. The source gases for the halogen radicals—the chlorofluorocarbons (CFCs)

and bromocarbons—are principally anthropogenic. The amount of the radicals can

be strongly affected by reactions on the surface of stratospheric aerosols and even

more profoundly affected in the polar winter by reactions on the surface of polar

stratospheric clouds (PSCs).

The annual cycle of total ozone is largely driven by transport effects. For

example, large-scale waves present in the winter stratosphere have the effect of

building up ozone levels in the higher winter latitudes.

Clearly, variability in ultraviolet radiation reaching the Earth leads to changes

in global total ozone. For example, from 1986 to 1990 the solar UV increased with

the onset of the 11-year solar cycle and resulted in an increase of global total ozone

of almost 2%. Energetic particle flux from the sun may also drive natural ozone

variations in the mesosphere and upper stratosphere.

Both two-dimensional (2D) and three-dimensional (3D) models are used by

several research groups for studies of ozone behavior. Although these models give

reasonable agreements with many aspects of ozone measurements, they are still

lacking in some important respects. For instance, the 2D models have not been able

to provide accurate representations of the ozone trends that were observed in middle

and high latitudes over the 1980-1990 time period. The 3D models suffer from

unrealistic temperature fields which, in turn, alter the photochemistry.

Major Scientific Issues

The major scientific issues in regard to our understanding of ozone phenomena are

divided into natural changes and human-made changes. Separating these components is the goal of much ozone and trace gas research.

The natural changes to be dealt with have been cited before. They include

the interannual and long-term variability of the stratospheric circulation; the changes

in external influences such as solar and

energetic particles; and changes in natural aerosols by volcanic eruptions and

changes in PSC amounts due to

interannual variations in polar stratospheric temperatures

Human-made changes are principally those associated with the release

into the atmosphere of unreactive chlorine- and bromine-containing compounds such as the CFCs. Aviation also

has an impact on ozone through the release of nitrogen radicals in aircraft exhaust.

63 ̊-90 ̊ total ozone average
44 EOS SCIENCE PLAN

Required Measurements and Data Sets

The minimum measurement requirements, and the EOS instruments which will

make the measurements, are shown in the table. Often key measurements are to be

made by more than one instrument giving the whole measurement suite a desirable

level of robustness in case of instrument failure.

Required measurements must satisfy the need for meteorological information; the need for chemical information including both chemical and dynamical

measurements in both the stratosphere and troposphere; the need for stratospheric

aerosol and PSC information; and the need for solar-ultraviolet flux determinations. In addition, there must be a concerted effort at validating the satellite

measurements.

EOS Contributions

There are many potential EOS contributions to the understanding of changes in

stratospheric ozone. The contributions will be in meteorological measurements,

chemical measurements, aerosols, solar ultraviolet flux, and advanced modeling

techniques. Just a few of the improvements are mentioned here.

O3 0.2 ppm MLS, HIRDLS, SAGE III

H2

O 0.5 ppm MLS, HIRDLS, SAGE III

CFC-11 / 12 0.2 ppb HIRDLS

N2

O 20 ppb MLS, HIRDLS

CH4 0.1 ppm HIRDLS

HCl 0.1 ppb MLS

C1ONO2 0.1 ppb HIRDLS

HNO3 1.0 ppb HIRDLS, MLS

NO2 / NO 0.2 ppb HIRDLS, SAGE III

C1O 50 ppt MLS

BrO 5 ppt MLS

OH 0.5 ppt MLS

N2

O5 0.2 ppb HIRDLS

Aerosols Surface area within 10% SAGE III, HIRDLS

Solar Flux 100-400 nm to 4% SOLSTICE

Meteorology

Stratospheric chemical and dynamical measurement requirements. Requirements include vertical resolution of 1-2 km through

the tropopause into the lower

stratosphere. Horizontal resolution is minimally that of UARS

(2700 km), but increased horizontal resolution vastly improves the

science. HIRDLS scanning will

achieve a horizontal resolution of

400 km. AMLS may achieve a horizontal resolution of 100 km with

MMIC array technology.

MEASUREMENT ACCURACY EOS INSTRUMENT

Temperature 1K MLS, HIRDLS, SAGE III

Winds 2-5 m/s (none)

Chemistry
Chapter 7 Executive Summary 45

EOS limb sounders (Microwave Limb Sounder [MLS] and High-Resolution Dynamics Limb Sounder [HIRDLS]) will greatly improve the accuracy,

precision, and resolution of temperature measurements in the tropopause region. HIRDLS will provide higher horizontal resolution temperature profiles

than have been available heretofore. MLS will provide hydroxyl (OH) measurements that were not previously available. The Stratospheric Aerosol and

Gas Experiment III (SAGE III) instrument will provide many advances, including the first satellite measurements of the size distribution of PSCs. Fully

interactive chemical dynamical models are being developed especially for interpretation of EOS data. Wind fields provided by the NASA/GSFC Data

Assimilation Office are of sufficient quality to remove the dynamical uncertainty from tracer observations.
46 EOS SCIENCE PLAN

Chapter 8

Volcanoes and Climate Effects of Aerosols

Introduction

Chapter 8 focuses on volcanoes, volcanic eruptions that inject gases and particles

into the atmosphere, the conversion of volcanic gases into aerosols, and on stratospheric and tropospheric aerosols more generally as they interact with climate. Major

sections of this chapter discuss: explosive volcanic eruptions and how they may

lead to stratospheric aerosols that have climatic effects, and tropospheric aerosols,

their sources, and their important climatic effects. A brief review is included of

other types of volcanic hazards, hazard prevention, preparedness, and relief measures. A second section treats the measurements and data sets that are required to

improve understanding of the impacts of stratospheric and tropospheric aerosols. A

final section sets forth the anticipated EOS contributions to scientific knowledge

and the national benefit to be derived from the volcanology and aerosol research

performed as parts of EOS.

Background Information

Volcanic emissions can cause significant variations of climate on a variety of time

scales—just one very large eruption can cause a measurable change in the Earth’s

climate with a time scale of a few years. Sulfur dioxide released from the magma

may be oxidized to sulfuric acid aerosols in the stratosphere, which may reside

there for a year or more, generally producing cooling at the Earth’s surface. In

performing research on global change it is important to distinguish climate effects

of natural phenomena such as volcanic aerosols from those effects due to human

activities.

Stratospheric aerosols produced by volcanic eruptions can influence stratospheric chemistry both through chemical reactions that take place on the surface of

the aerosols and through temperature changes induced by their presence in the stratosphere.

A wide variety of aerosol types is found in the troposphere, including sea

salt and dust carried from the surface into the atmosphere by winds, and aerosols

formed by chemical transformations from gaseous to liquid or solid forms. Volcanic eruptions can also contribute to tropospheric aerosols, and there are other natural

sources including biogenic particles and products from natural fires. Aerosols contributed by humans have been increasing, particularly those associated with SO2

from combustion of fossil fuels and from biomass burning. The primary effect of

these anthropogenic aerosols on the Earth’s energy balance is a cooling of about

-0.5 Wm-2 compared to the forcing associated with the change in greenhouse gases
Chapter 8 Executive Summary 47

during the industrial age of about +2 Wm-2. Subsonic aircraft flying in the lower

stratosphere are also a source of aerosol particles.

Accurate measurements of aerosols are also needed to provide corrections

for remote sensing of Earth surface properties.

Major Scientific Questions and Hypotheses

Major scientific questions to be dealt with at this time have to do with: stratospheric

volcanic aerosols and their effect on climate, the “sulfur budget” of individual eruptions, which defines the percentage of gas dissolved in the melt that is released in

the eruption, the role of volcanic aerosols in ozone depletion, tropospheric aerosols

and their effect on climate, and volcanic hazards.

Stratospheric volcanic aerosols have had a

well-documented effect of inducing climate cooling. The “year without a summer” (1816) is clearly

associated with the eruption of Tambora in Indonesia in April 1815. The recent Mt. Pinatubo eruption

(1991) is associated with Northern Hemisphere surface cooling of as much as 0.5 ̊C.

Sulfur dioxide (SO2) from volcanic emissions

is recognized as the major contributor to stratospheric aerosols. In the atmosphere it converts to

sulfuric acid (H2SO4) via the OH radical. The amount

of stratospheric aerosols and their effects on climate

depend on the ability of the eruption to inject material into the stratosphere and on the sulfur content

of the emissions. However, microphysical properties of the aerosol particles must be taken into

account in reckoning whether their infrared absorptivity, which acts to warm the Earth, or their albedo

effect, which acts to cool the Earth, will be dominant.

The presence of volcanic aerosols in the

stratosphere has recently been tied to depletion of

stratospheric ozone in temperate latitudes. The concept is that sulfate aerosols serve as sites for

heterogeneous chemical reactions which have the

effect of destroying ozone.

Tropospheric aerosols affect the radiative

forcing of climate through three primary mechanisms: 1) Direct forcing in which radiation is

scattered or absorbed by the aerosol particles; 2)

indirect forcing in which enhanced concentrations

of aerosol particles result in enhanced concentrations of cloud drops; and 3) the indirect effects of

Combined forcing (CO2 + SO4 + Dust) -.60

CO2 + SO4 (anthropogenic increase since 1950) .36

Dust (from distributed soils) -.96

Surface forcing caused by

dust from disturbed soils is

currently on the order of

-1 Wm-2, which is comparable

in magnitude to the current effect of CO2 and sulfate

aerosols (Tegen et al., 1996).
48 EOS SCIENCE PLAN

aerosols on heterogeneous atmospheric chemistry (not discussed further in this chapter).

The direct radiative effects on climate of tropospheric aerosols are hard to

assess because of the wide range of chemical compositions, time and spatial distributions, range of particle sizes and shapes, interactions with water vapor and clouds,

and overall global variability that is dependent on both natural sources and human

activities. Assessments of the indirect effects of tropospheric aerosols are even more

difficult to make, yet they may be as significant as the direct effects.

Volcanoes pose significant hazards for people and property on the ground,

and the major challenge to satellite-based observations of volcanic hazards is the

development of techniques that can be used in a predictive manner to detect an

evolving volcanic crisis and to provide timely information to the relevant authorities on the ground. Thermal and deformation monitoring of numerous volcanoes

that show signs of activity will be undertaken during the EOS era. The hazards

associated with eruptions are diverse and numerous, and include the health hazards

associated with low-altitude volcanic gases, and loss of life and property by inundation by lava flows, pyroclastic flows, and mud flows. There is also an increasingly

frequent potential for unexpected aircraft encounters with volcanic plumes or clouds,

with the potential catastrophic loss of life due to a major air crash.

Required Measurements and Data Sets

Measurements are required to assess the climate roles of stratospheric aerosols,

tropospheric aerosols, and volcanic aerosol precursor gases, and to assess volcanic

hazards.

For climate monitoring and prediction purposes, the stratospheric aerosol

loading between 40 km and the tropopause should be measured. Column optical

depth should be measured with a horizontal spatial resolution of 400 km and accuracy of 0.001. The vertical resolution should be 1 km. For tropospheric aerosols,

the optical depth accuracy should be 0.01, and there should be measurements of

particle size and vertical distribution. The primary volcanic gas associated with

aerosol formation, sulfur dioxide,

should be measured with 5-10%

accuracy. For detection and avoidance of volcanic hazards, there

should be measurements of plume

altitude, dispersal rate, water vs.

ash content, and plume temperature. For volcanic hazards on the

ground, ground deformation at the

cm-scale should be measured,

along with thermal flux from active lava flows, lava lakes, and

fumarole fields to an accuracy of

~104 Wm-2. Surface topography

should be measured at a spatial 0 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13.00 14.00 15.00

Map of the Mt. Pinatubo SO2

cloud from MLS (Read et al.,

1993).
Chapter 8 Executive Summary 49

scale of ~25 m/pixel and vertical accuracy of ~5 m in order to aid in the numerical

modeling of surface flows, i.e., lava, pyroclastic, or mud flows, and in the analysis

of slope stability.

EOS Contribution: Expected Improvement in Knowledge and

National Benefit

EOS will make considerable contributions to our knowledge of volcanic eruptions

and their consequences for climate change. MODIS, MISR, ASTER, and ETM+

will be used to characterize the number, location, style, and duration of both lavaproducing and explosive eruptions. Plume-top altitudes and topography provided

by MODIS, ASTER, HIRDLS, and MISR will allow testing of physical models of

plume rise and dispersal. Volcano topography will be derived from ASTER, VCL

(Vegetation Canopy Lidar) and foreign-partner radars. Measurements of different

aspects of sulfur dioxide abundance will be made by TOMS, OMI, TES, MLS, and

ASTER. Several EOS instruments, SAGE III, EOSP, MISR, OMI, GLAS, and

HIRDLS, will monitor stratospheric and tropospheric aerosols. Continuous measurements made by MODIS, CERES, and SAGE III will provide an important record

of the effects of volcanic aerosols on the Earth’s radiation budget and on global

vertical profiles of atmospheric temperature and composition. GLAS on the EOS

ICESat spacecraft and VCL will provide valuable information on the vertical and

spatial extent of significant stratospheric and tropospheric aerosol layers.

Overall, the contribution of EOS will be to provide the global data necessary

to allow understanding and prediction of aerosol changes as an essential aspect of

assessing the causes of climate variability and climate change. EOS measurements

will also enable the first truly global inventory of volcanic eruptions, as well as the

high-temporal-resolution study of surface flows and eruption plumes in the stratosphere. Through a combination of multiple EOS instrument measurements, volcano

hazard mitigation will also be improved because of the dramatic increase in the

quantitative measurement of lava temperatures, gas emissions, surface topography,

eruption plume tracking, and ground deformation.

Some EOS stratospheric aerosol products

SAGE-III Aerosol 1/km 5% :: 5% 1 profile/ <2 × <1 deg :: 1 km :: 0-40 km

Extinction Profiles (2 min), Global

(7 wavelengths) 30/day

HIRDLS 1/km 5-10% :: 2 global 400 × 400 km :: 1 km :: 5-60 km

Aerosol Extinction 1-10% maps Global (given accuracies

Coefficient /day [d, n] for 7-30 km)

 PARAMETER UNITS ACCURACY TEMPORAL HORIZONTAL VERTICAL COMMENTS

 NAME ABS::REL RESOLUTION RESOL:: COVER RESOL::COVER
 ACRONYMS 51

ACRONYMS

2D Two Dimensional

3D Three Dimensional

4DDA 4-Dimensional Data Assimilation

A/SA arid/semi-arid

AABW Antarctic Bottom Water

AASE II Airborne Arctic Stratospheric

Expedition II

AATSR Advanced Along Track Scanning

Radiometer

ACRIM I Active Cavity Radiometer Irradiance

Monitor I

ACSYS Arctic Climate System Study

ADEOS Advanced Earth Observing System

AEAP Atmospheric Effects of Aviation

Program

AERONET Aerosol Robotic Network

AESOPS Antarctic Environment Southern

Ocean Process Study

AGCM atmospheric general circulation models

AHM (model)

AIRS Atmospheric Infrared Sounder

AIRSAR Airborne Synthetic Aperture Radar

ALOS Advanced Land Observation Satellite

ALT Altimeter

AMI Active Microwave Instrument

AMIP Atmospheric Model Intercomparison

Project

AMLS Array MLS

AMSR Advanced Microwave Scanning

Radiometer

AMSR-E Advanced Microwave Scanning

Radiometer (EOS Version)

AMSU Advanced Microwave Sounding Unit

APAR Absorbed Photosynthetically-Active

Radiation

ARM Atmospheric Radiation Measurement

ASAR Advanced Synthetic Aperture Radar

ASF Alaska SAR Facility

ASTER Advanced Spaceborne Thermal

Emission and Reflection Radiometer

ATBD Algorithm Theoretical Basis Document

ATLAS Atmospheric Laboratory for Applications

and Science

ATMOS Atmospheric Trace Molecule Spectroscopy

ATSR Along Track Scanning Radiometer

AVHRR Advanced Very High-Resolution

Radiometer

AVIRIS Airborne Visible-Infrared Imaging

Spectrometer

AWS Automatic Weather Stations

BAHC Biospheric Aspects of the Hydrological

Cycle

BATS Biosphere-Atmosphere Transfer Model

BIOME Biogeochemical Information Ordering

Management Environment

BOREAS Boreal Ecosystems Atmosphere Study

BRDF bidirectional reflectance distribution

function

BSRN Baseline Surface Radiation Network

BUV Backscatter Ultraviolet

CALM Circumpolar Active Layer Monitoring

CART Cloud and Radiation Testbed

CASES Cooperative Atmosphere-Surface

Exchange Study

CCD Charge-Coupled Device

CCN Cloud Condensation Nuclei

CDIAC Carbon Dioxide Information and Analysis

Center

CDOM Colored Dissolved Organic Matter

CEM cumulus ensemble model

CERES Clouds and the Earth’s Radiant Energy

System

CESBIO Centre d’Études Spatiales de la Biosphère

CFC Chlorofluorcarbon

CH2Cl2 Dichloromethane

CH3Cl Methyl chloride

CHCl3 Chloroform

CHEM-1 Chemistry Mission-1

CLAES Cryogenic Limb Array Etalon

CLASS Canadian Land Surface Scheme

CLIVAR CLImate VARiability and prediction

ClOx oxides of chlorine family

CMDL Climate Monitoring and Diagnostics

Laboratory

A

B

C
52 ACRONYMS

COARE Coupled Ocean-Atmosphere Response

COS Carbonyl Sulfide

COSEPUP Committee on Science, Engineering, and

Public Policy

COV Coefficient of Variation

CPR Cloud Profiling Radar

CR Correlation Radiometry

CRYSYS Use of the Cryospheric System to Monitor

Global Change in Canada (EOS IDS)

CTM Chemistry and Transport Model

CZCS Coastal Zone Color Scanner

DAAC Distributed Active Archive Center

DAO Data Assimilation Office

DAS Data Assimilation System

DDL Direct Downlink

DECAFE Dynamique et Chimie de l’Atmosphere en

Foret Equatoriale

DEM Digital Elevation Model

DFA Dual-Frequency radar Altimeter

DIC Dissolved Inorganic Carbon

DMS Dimethyl Sulfide

DMSP Defense Meteorological Satellite Program

DOC Dissolved Organic Carbon

DoD Department of Defense

DoE Department of Energy

DOM Dissolved Organic Matter

DORIS Doppler Orbitography and

Radiopositioning Integrated by Satellite

DT Delta T (Temperature)

DU Dobson Unit

ECHIVAL European International Project on Climate

and Hydrological Interactions between

Vegetation, Atmosphere, and Land Surfaces

ECLIPS Experimental Cloud Lidar Pilot Study

ECMWF European Centre for Medium-Range

Weather Forecasts

EDC EROS Data Center

EFEDA ECHIVAL Field Experiment in Desertification-Threatened Areas

EGIG Expédition Glaciologique Internationale

au Groenland

ENSO El Niño-Southern Oscillation

ENVISAT Environmental Satellite, ESA

EOS Earth Observing System

EOS PM EOS afternoon-crossing satellite

EOSDIS EOS Data and Information System

EOSP Earth Observing Scanning Polarimeter

EP Earth Probe

ER-2 NASA Research Aircraft

ERB Earth Radiation Budget

ERBE Earth Radiation Budget Experiment

ERBS Earth Radiation Budget Satellite

EROS Earth Resources Observation System

ERS European Remote-Sensing Satellite

ERS-1 European Remote-Sensing Satellite-1

ESA European Space Agency

ESCC Electrically Self-Calibrating Cavity

ESMR Electronically Scanning Microwave

Radiometer

ESSC Earth System Sciences Committee

ET Evapotranspiration

ETM Enhanced Thematic Mapper

ETM+ Enhanced Thematic Mapper Plus

EURECA European Retrievable Carrier

FAA Federal Aviation Administration

FAO Food and Agriculture Organization

FAPAR Fraction Absorbed Photosynthetically

Active Radiation

FIFE First ISLSCP Field Experiment

FIRE First ISCCP Regional Experiment

FLUXNET Flux Network

FPAR Fraction of Photosynthetically-Active

Radiation

FSSP Forward Scattering Spectrometer Probe

FTS Fourier Transform Spectrometer

GAIM Global Analysis, Interpretation, and

Modeling

GAP Gap Analysis Project

GCIP GEWEX Continental-Scale International

Project

D

E

F

G
 ACRONYMS 53

GCM General Circulation Model (also Global

Climate Model)

GCOS Global Climate Observing System

GCTE Global Change in Terrestrial Ecosystems

GEBA Global Energy Balance Archive

GENESIS Global Environmental and Ecological

Simulation of Interactive Systems

GEOS Goddard Earth Observing System

GERB Geostationary Earth Radiation Budget

GEWEX Global Energy and Water Cycle Experiment

GFDL Geophysical Fluid Dynamics Laboratory

GFO Geosat Follow-On

GGD Global Geocryology Database

GHCN Global Historical Climatology Network

GIS Geographic Information System

GISP Greenland Ice Sheet Program

GISS Goddard Institute for Space Studies

GLAS Geoscience Laser Altimeter System

GLCTS Global Landcover Test Site Initiative

GLI Global Imager

GLIMS Global Land Ice Monitoring from Space

GLOBE Global Learning and Observations to Benefit

the Earth

GLOBEC Global Ocean Ecosystem Dynamics

GMS Geostationary Meteorological Satellite

GNP Gross National Product

GOALS Global Ocean-Atmosphere-Land System

GOES Geostationary Operational Environmental

Satellite

GOMOS Global Ozone Monitoring By Occultation of

Stars

GPCP Global Precipitation Climatology Project

GPP Gross Primary Productivity

GPS Global Positioning System

GRDC Global Runoff Data Center

GSFC Goddard Space Flight Center

Gt Gigaton

GTOS Global Terrestrial Observing System

GVaP GEWEX Water Vapor Project

HALOE Halogen Occultation Experiment

HAPEX Hydrological-Atmospheric Pilot Experiment

HCFC Hydrochlorofluorocarbon

HH Horizontal, Horizontal Polarization

HIRDLS High-Resolution Dynamics Limb Sounder

HIRS High-Resolution Infrared Radiation Sounder

HNLC High Nutrient, Low Chlorophyll

HOX odd hydrogen family

HRDI High-Resolution Doppler Imager

HSB Humidity Sounder, Brazil

HSCT High-Speed Civil Transport

IABP International Arctic Buoy Program

ICESat Ice, Clouds, and Land Elevation Satellite

ICRCCM Intercomparison of Radiative Codes for

Climate Models

ICSU International Council of Scientific Unions

IDS Interdisciplinary Science Investigation (EOS)

IFC Intensive Field Campaign

IFO intensive field observation

IFOV Instantaneous Field of View

IGAC International Global Atmospheric Chemistry

IGBP International Geosphere-Biosphere

Programme

IGPPDI Global Primary Production Data Initiative

IHP International Hydrological Program

ILAS Improved Limb Atmospheric Spectrometer

IMAS Integrated Multispectral Atmospheric

Sounder

IOC Intergovernmental Oceanographic Commission

IOP Intensive Observing Period

IPCC Intergovernmental Panel on Climate Change

IR infrared

ISAMS Improved Stratospheric and Mesospheric

Sounder

ISCCP International Satellite Cloud Climatology

Project

ISLSCP International Satellite Land Surface Climatology Project

IT Instrument Team

ITCZ Inter-Tropical Convergence Zone

IWP ice water path

JERS Japanese Earth Remote-Sensing Satellite

JERS-OPS Japanese Earth Remote-sensing SatelliteOPS

JGOFS Joint Global Ocean Flux Study

H

I

J
54 ACRONYMS

JPLAIRSAR JPL Airborne Synthetic Aperture Radar

JPO Joint Planning Office

KINEROS Kinematic wave overland flow, channel

routing and Erosion model

LAI Leaf-Area Index

Landsat Land Remote-Sensing Satellite

LBA Large Scale Biosphere-Atmosphere

Experiment in Amazonia

LERTS Laboratoire d’Etudes et de Recherches en

Teledetection Spatiale

LHH L-band HH

LIS Lightning Imaging Sensor

LITE Lidar In-space Technology Experiment

LOICZ Land Ocean Interactions in the Coastal Zone

LS Lower Stratosphere

LSM Land-Surface Model

LSP Land-Surface Parameterizations

LTER Long-Term Ecological Research

LW longwave

LWP liquid water path

MAAT Mean Annual Air Temperatures

MAPS Measurement of Air Pollution from Satellites

MCS mesoscale convective systems

MERIS Medium-Resolution Imaging Spectrometer

METEOR-3 Russian Operational Weather Satellite

METOP Meteorological Operational Satellite

MHS Microwave Humidity Sounder

MIMR Multifrequency Imaging Microwave

Radiometer

MISR Multi-angle Imaging Spectroradiometer

MIT Massachusetts Institute of Technology

MLS Microwave Limb Sounder

MM mesoscale model

MMIC Microwave Monolithic Integrated Circuit

MMS Modular Modeling System

MODIS Moderate-Resolution Imaging

Spectroradiometer

MODLAND MODLIS Land

MOPITT Measurements of Pollution in the Troposphere

MOU Memorandum of Understanding

MSG Meteosat Second Generation

MSU Microwave Sounding Unit

MT Megaton

MVI MODIS Vegetation Index

NAD Nitric Acid Dihydrate

NADW North Atlantic Deep Water

NASA National Aeronautics and Space Administration

NASDA National Space Development Agency

NAT Nitric Acid Trihydrate

NBIOME Northern Biosphere Observation and

Modeling Experiment

NCAR National Center for Atmospheric Research

NCDC National Climatic Data Center

NCEP National Centers for Environmental

Prediction

NDVI Normalized Difference Vegetation Index

NESDIS National Environmental Satellite, Data, and

Information Service

NEXRAD Next Generation Weather Radar

NH Northern Hemisphere

NIR Near Infrared

NMC National Meteorological Center

NMHC Non-Methane Hydrocarbons

NOAA National Oceanic and Atmospheric Administration

NOPEX Northern Hemisphere Climate-Processes

Land-Surface Experiment

NOX odd nitrogen family

NPOESS National Polar-orbiting Operational

Environmental Satellite System

NPP Net Primary Production

NRC National Research Council

NSCAT NASA Scatterometer

NSF National Science Foundation

NSIDC National Snow and Ice Data Center

NWP Numerical Weather Prediction

K

L

M

N
 ACRONYMS 55

OCS Carbonyl Sulfide

OCTS Ocean Color and Temperature Scanner

OH Hydroxyl

OLR Outgoing Longwave Radiation

OMI Ozone Measuring Instrument

ONR Office of Naval Research

ORNL Oak Ridge National Laboratory

OSU Oregon State University

OTTER Oregon Transect Terrestrial Ecosystem

Research

PAR Photosynthetically-Active Radiation

PARCA Program for Arctic Regional Climate

Assessment

PEM Production Efficiency Model

PI Principal Investigator

PIK Potsdam Institute for Climate Impact

Research

PILPS Project for Intercomparison of Land-Surface

Parameterization (LSP) Schemes

PNZ Phytoplankton-nutrient-zooplankton

POLDER Polarization and Directionality of the Earth’s

Reflectance

POLES Polar Exchange at the Sea Surface (IDS)

ppm parts per million

PR Precipitation Radar

PSC Polar Stratospheric Cloud

PSU Pennsylvania State University

PW precipitable water

QBO Quasi-Biennial Oscillation

Radarsat Radar Satellite, Canada

RAMS Regional Atmospheric Modeling System

RC radiative-convective

REP Relativistic Electron Precipitation

RGPS Radarsat Geophysical Processor System

S.D. Standard Deviation

SAFARI South African Fire—Atmospheric Research

Initiative

SAGE Stratospheric Aerosol and Gas Experiment

SALSA Semi-Arid Land-Surface-Atmosphere

SAM Stratospheric Aerosol Measurement

SAR Synthetic Aperture Radar

SAVI Soil-Adjusted Vegetation Index

SBUV Solar Backscatter Ultraviolet

SCA Snow-Covered Area

SCANSAR Scanning Synthetic Aperture Radar

SCAR-B Smoke Cloud and Radiation-Brazil

SCARAB Scanner for Radiation Budget

SCF Science Computing Facility

SCICEX Submarine Arctic Science Cruise (Program)

SCOPE Scientific Committee on Problems of the

Environment

SeaWiFS Sea-viewing Wide Field-of-view Sensor

SEB Surface Energy Balance

SEDAC Socioeconomic Data and Applications Center

SGP Southern Great Plains

SHEBA Surface Heat Budget of the Arctic Ocean

SiB Simple Biosphere Model

SIMIP Sea Ice Model Intercomparison Project

SIR-C Shuttle Imaging Radar-C

SLR Satellite Laser Ranging

SMM Solar Maximum Mission

SMM/I Special Sensor Microwave/Imager

SMMR Scanning Multispectral Microwave Radiometer

SOHO Solar Heliospheric Observatory

SOLAS Surface Ocean Lower Atmosphere Study

SOLSTICE Solar Stellar Irradiance Comparison

Experiment

SPCZ South Pacific Convergence Zone

SPE Solar Particle Event

SPOT Systeme pour l’Observation de la Terre

SRB Surface Radiation Budget

SRBEX Susquehanna River Basin Experiment

SSALT Solid State radar Altimeter

SSM/I Special Sensor Microwave/Imager

SST Sea-Surface Temperature

SSU Stratospheric Sounding Unit

STP Standard Temperature and Pressure

STS Space Transport System

386

O

P

Q

R

S
56 ACRONYMS

SVAT Soil-Vegetation-Atmosphere Transfer Model

SVI Spectral Vegetation Indices

SW shortwave

SWE Snow Water Equivalent

SWIR Shortwave Infrared

T-S temperature-salinity

TARFOX Tropospheric Aerosol Radiative Forcing

Observational Experiment

TEM Terrestrial Ecosystem Model

TES Tropospheric Emission Spectrometer

THM Terrestrial Hydrology Model

TIR Thermal Infrared

TM Thematic Mapper

TMI TRMM Microwave Imager

TMR TOPEX Microwave Radiometer

TOA top of the atmosphere

TOGA Tropical Ocean Global Atmosphere

TOMS Total Ozone Mapping Spectrometer

TOP Terrestrial Observation Panel

TOPEX/ Ocean Topography Experiment

Poseidon

TOPORAD (model)

TOPSAR Topographic Synthetic Aperture Radar

TOVS TIROS Operational Vertical Sounder

TRACE-A Transport and Chemistry near the Equator

over the Atlantic

TRAGNET United States Trace Gas Network

TRMM Tropical Rainfall Measuring Mission

TSI total solar irradiance

UARS Upper Atmosphere Research Satellite

UKMO United Kingdom Meteorological Office

UMCP University of Maryland, College Park

UNEP United Nations Environment Program

UNESCO United Nations Educational, Scientific, and

Cultural Organization

USAF United States Air Force

USDA United States Department of Agriculture

USGCRP U.S. Global Change Research Program

USGS United States Geological Survey

UT Upper Troposphere

UV Ultraviolet

UV-B Ultraviolet-B

VEMAP Vegetation/Ecosystem Modeling and

Analysis Project

VHRR Very High Resolution Radiometer

VI Vegetation Index

VIC Variable Infiltration Capacity

VIRGO Variability of solar Irradiance and Gravity

Oscillations

VIRS Visible Infrared Scanner

VIS Visible

VNIR Visible and Near Infrared

VOC Volatile Organic Carbon

WCRP World Climate Research Program

WDC-A World Data Center-A

WFPS Water-Filled Pore Space

WMO World Meteorological Organization

WOCE World Ocean Circulation Experiment

WSR Weather Survelliance Radar

X-SAR X-Band Synthetic Aperture Radar

T

U

V

W

X
 INDEX 57

Page numbers in bold italics type can be found in the EOS Science Plan Executive Summary

2-D models 18, 317-318, 43

3-D models 18, 318-319, 43

4-D assimilation 32, 207, 30-31

4DDA (also see data assimilation)

204, 207, 216, 367

24 key variables 10, 9

A/SA 216, 238

AABW 123

AASE II 321

AATSR 67, 69, 365-366

absorption, scattering, and emission,

aerosol 50

absorption, scattering, and emission,

cloud 51-52

absorption, scattering, and emission,

Earth’s surface 52-55

absorption, scattering, and emission,

gas 49-50

ACRIM 8, 11, 22, 43-47, 66-67, 69,

91, 103, 9, 12, 19

ACSYS 20, 274, 297

ADEOS 14, 24-27, 69, 87, 89, 139,

366, 19, 21

AEAP 322

AERONET 370

aerosols 19, 27, 29, 31, 208, 315-316,

322, 325, 328, 330, 8, 13, 19, 42-

44, 46, 49

aerosol abundance 353-354

aerosol indirect effects of 355-358,

362-366, 47-48

aerosol measurements (see also

instrument names) 368-371

aerosol radiative effects 352-355

aerosol radiative properties 345-347

aerosol sources 349-354

aerosol, climate effects of 349-358,

370-372

aerosol, climate modification by 372

AESOPS 150

AGCMs (see GCMs)

agriculture 26, 30, 34-35, 179, 203,

206, 210, 213, 220, 230, 234,

238, 352, 358

Agung 48, 342

aircraft exhaust 26, 320, 322, 350, 43

aircraft hazards 361-362, 8

AIRS/AMSU/HSB 12-13, 21, 26-29,

31-32, 35, 50, 52, 55, 59, 62, 67-

71, 78-82, 94-99, 102, 105, 140-

141, 142, 210, 212, 217, 292,

367, 14, 16-18, 20-21, 39, 41

AIRSAR 176, 285

ALOS 236, 364-366

AMIP 55, 80, 86, 271, 282, 289

AMLS 326-329, 44

AMSR 55, 62, 75-76, 79, 87-88, 95,

97, 101, 104-105, 139-141, 152,

206, 212

AMSR-E 14-15, 18, 28-29, 35, 52, 62,

67, 72, 75-76, 79, 87-88, 96-100,

139, 151, 283, 289, 292-293,

298, 18-19, 21, 24, 35, 37, 39-41

anthropogenic aerosols (see aerosol

sources)

APAR 228, 234, 242

ARM 20, 50, 55, 72, 90, 91, 94, 102,

215, 217-218, 245, 22

assimilation data sets (see 4DDA)

ASTER 13, 17-19, 22, 29-31, 52-55,

66, 69, 72, 94, 96, 210, 213-214,

217, 234, 275, 285, 288, 290,

294-296, 298, 361, 364-368, 17,

20, 34-35, 40-41, 49

ATBD 176

ATLAS 44, 47

ATMOS 321

atmospheric chemistry (see also

greenhouse gases, CHEM-1) 15-

16, 7-8, 28-29, 31, 48

atmospheric circulation (see also

QuikSCAT, SeaWinds) 14, 87-

89, 96

atmospheric forcings 204

atmospheric temperature 21, 21-22,

49, 96-97, 101

ATSR 73, 362

AVHRR 28, 52, 66-67, 75, 87, 90, 94,

171, 206, 208, 221-229, 233,

239-240, 249, 284-288, 291,

294-298, 360, 362, 368-369, 13,

20, 34, 40-41

AVIRIS 213, 289

AWS 298

BAHC 213, 246, 249-250

BATS 201, 213

biodiversity 26, 33-34, 136, 249

biogenic aerosols (see aerosol sources)

biogeochemistry 136-138, 149, 156,

28, 32-33

biogeochemistry, river 222-223

biogeochemistry, terrestrial 231-232

biological threat 311

biomass burning 11, 15-16, 19, 29, 31,

34, 50, 176, 181, 184, 341, 350-

358, 370-371, 8, 13, 27-31, 46

BIOME2 175, 232, 252, 32

bio-optical measurements 1453

biospheric responses-dynamics 208-

209, 232

BOREAS 20, 237, 239, 241-244, 297

boundary layer fog 64

boundary layer cloud 64

BRDF 92, 207, 233-234, 243, 246

bromine 9, 314-315, 324, 329, 42-43

BSRN 20, 55, 70-71, 91, 102, 22

calibration 7-8, 21-25, 46-48, 66-69,

70-74, 82, 86, 90-94, 99, 102,

104, 129, 151, 205-206, 221,

226, 233-234, 237-239, 273,

292, 327, 331, 353, 366, 369-

370, 7, 18, 21

calibration strategy 23-25

CALM 285

Carbon America 247

INDEX

A B

C
58 INDEX

Page numbers in roman type can be found in the main EOS Science Plan

carbon cycle 16, 101, 117, 130, 132,

135, 150, 154, 156, 168, 170-

177, 181-188, 228-229, 231-232,

238, 241, 243, 246-249, 252, 24,

29-30

carbon dioxide (CO2) 7, 9, 11, 14-16,

18, 20, 23, 25, 28, 30-33, 48-49,

56, 59, 61, 65-66, 80, 84, 88, 91,

117, 130-136, 142-148, 153-156,

167-173, 176, 181, 184-190,

201-209, 219-238, 240-251, 270-

271, 274, 279, 286, 297, 311,

322, 348, 359, 369-370, 25-29

carbon monoxide (CO) 14-16, 22, 26,

31-35, 132, 154, 167-168, 178-

183, 187-190, 332, 359, 367, 12,

19, 27-31, 38

CART 102, 237-239, 245

CART-ARM 239, 245

CASES 239, 245

CCD 233, 246, 369

CCN 351, 354

CDIAC 174

CDOM (see DOM)

CEMs 63-64, 16

CERES 11, 13, 19, 21, 25, 28-29, 31-

32, 50-55, 62, 66-67, 69-71, 79,

92-94, 102, 104, 207, 210, 217,

295, 297, 367, 13-16, 19-20, 40-

41, 49

CESBIO 251

CFC 314, 321, 326, 44

CH2Cl2 321

CH3Cl 182, 314, 321

CHCl3 321

CHEM-1 (see also ozone, see also

specific sensor names) 16, 347,

368

chemistry, stratospheric (see CHEM-1)

chemistry, tropospheric 22

chlorine 9, 18, 25-27, 312-327, 333,

349, 42-43

chlorophyll _ a (see phytoplankton)

CLAES 331, 346, 347

CLASS 275

climate change 311, 28, 32, 36, 40-42

climate change, long term 30-33

CLIVAR 20, 101-102, 149, 18-22

Clx 315, 322

cloud modeling 59-63

cloud observations 57-58

cloud property measurements 72, 94,

104

clouds 12, 21, 25, 8, 10-16, 19-25, 35,

42-43, 48

clouds, aerosol effects on (see aerosol

indirect effects)

clouds, marine 57

CMDL 247, 250

CO2 7, 9, 11, 14-16, 18, 20, 23, 25,

28, 30-33, 48-49, 56, 59, 61, 65-

66, 79, 84, 87, 90-91, 117, 130-

135, 141-148, 154-156, 167-173,

176, 181, 184-190, 201-209,

219-238, 240-251, 270-271, 274,

279, 286, 297, 311, 322, 348,

359, 369-370, 25-29

CO2 fluxes 132, 143, 156

COARE 63-64, 83, 101, 140, 149

coastal zone 35

coccolithophorid 145-146

continuity 23-25

convection 12-13, 43-45, 56-58, 62-

65, 77-83, 87, 104-106, 121-123,

149, 151, 169, 173, 179, 251,

279, 344, 14-18, 25, 28, 38

convection and clouds in climate

models 56, 80, 82

coral reefs 136, 148-149

COS 190, 343, 364, 367

COSEPUP 372

COV 266

CPR 52, 91

CR 183

cryosphere 17-18, 237, 240, 263-267,

271, 278-279, 281, 284, 286,

298-299, 8, 36-38

cryosphere albedo 264

cryosphere-EOS instruments-measurements 264-266, 287-298

cryosphere-EOS interdisciplinary

investigations 298

cryosphere-freshwater 279

cryosphere modeling 264, 271-278,

280-281

cryosphere-related programs-ACSYS,

BOREAS, PARCA, SCICEX,

SHEBA 297

cryosphere-sea-level rise 263

cryosphere-thermal diffusivity 264

cryosphere volume 264-266

cryospheric climate linkage 264, 278-

279

cryospheric variability 266, 281-287

CRYSYS 240, 268, 290, 298

cyanobacteria 144-146

CZCS 145-146, 154

DAAC 68-69, 299, 15, 35

DAO 19, 206, 210, 218, 228, 236, 333

DAS 79, 215

data assimilation 55-57, 79, 81, 89,

97, 17, 45

DECAFE 181

DEC-CEN 20

DEM 218, 273, 289, 359, 361, 365,

365

DFA 99, 141, 143

DIC 146

diurnal sampling 21, 23, 10

DMS 145, 154, 350

DMSP 25, 75, 88, 139, 291

Dobson units 312

DOC (see DOM)

DoD 90, 139-140

DoE 20, 102, 236, 239, 245, 22

DOM 136, 143-146, 153

DORIS 142

droughts 221, 230, 7, 33

DT 177

DU 312, 314, 319

Earth’s energy balance, cloud effects

on 56-57

ECHIVAL (see EFEDA)

ECLIPS 20, 102, 22

ECMWF 56, 81, 89, 204, 210

ecosystem 20, 26, 30, 33-34, 128, 132-

137, 144, 146, 154-155, 168,

178, 187, 202-204, 214, 218,

225, 228-231, 235-238, 243-244,

247-251, 267, 270, 283, 297-

298, 29

D

E
 INDEX 59

Page numbers in bold italics type can be found in the EOS Science Plan Executive Summary

EDC 54, 69, 72, 234-235

EFEDA 244

EGIG 270

El Chichón 342-344

El Niño 15, 23-24, 28, 33, 52, 79, 83,

100, 119, 121, 124, 129, 173,

201, 212, 231, 247, 315, 322,

342, 344, 367, 25

energetic particles (see also SPEs,

REPs) 316-317, 319, 42-43

ENSO 15, 52, 79, 85-87, 103, 128,

132, 134, 136-137, 145, 148-

150, 154-155, 173, 212, 221,

344, 25

ENVISAT 66, 69, 73, 129, 139-140,

359, 364-367

EOS instrument products (see also

named instruments) 205-206,

208

EOS AM 12, 22, 25, 49, 52-54, 66-70,

92, 101-102, 179, 204, 208, 217,

223, 233, 240, 356, 369-371, 16,

19, 27

EOS PM 14, 55, 66, 75, 82, 88, 92,

101, 139, 212, 214, 18-19

EOSDIS 48, 86, 214, 218, 233, 236,

251, 299

EOSP 11, 13, 19, 29, 31-32, 50, 52,

59, 62, 67, 72, 75-79, 94-97,

102, 104-105, 208, 353, 356,

363-364, 366-371, 13-14, 17, 20,

49

EP 368

ER-2 327

ERB 8, 43-48, 54, 67-68, 12, 14-15

ERBE 11-12, 21, 44, 49, 51-56, 59,

66-70, 89, 281, 343, 346, 13-16

ERBS 44, 46-47

EROS 234

ERS 27-28, 30, 120, 129, 131, 140,

171, 176-177, 215, 236, 241,

285, 288, 291, 294-297, 360, 366

ESA 23, 27, 46, 66, 72, 87, 139-140

ESCC 43

ESMR 87

ESSC 7, 7

ETM+ (see Landsat-7) 17-19, 22, 234-

235, 294-295, 367-368, 34, 49

EURECA 44

evapotranspiration (ET) 188, 209-214,

222-225, 233-234, 239, 244,

246, 251, 33

extreme hydrologic events-severe

storms, floods, droughts 218-

222

FAA 360-361

FAO 216-217

FAPAR 172, 181

field campaigns (see also specific

names) 20, 358, 7, 10, 22

FIFE 205-206, 209-210, 214, 228,

237-239, 243

FIRE 20, 64, 70-76, 94, 100-101, 22

fires 22, 206, 29, 34-35, 39-40, 49

floodplains 177, 220-222

fluxes, radiative 48, 50, 52, 54, 65-66,

71-72, 91, 93, 97, 102, 104-105,

12-17, 19-20, 22-25

fluxes, surface 48-49, 52, 54, 65, 67-

70, 79, 83, 93, 104

fluxes, TOA 51, 59, 66-72, 92-93, 104

fluxes, within atmosphere 71-73

FLUXNET and EUROFLUX 241,

246-247

foreign partners 333

FPAR 206, 210, 214, 223, 225-226,

246

Franklin, Benjamin 349

freshwater cycle 279

freshwater forcing 121-123, 25, 27,

37-38

freshwater resources 35

frozen ground (permafrost) 269, 275,

295-296, 35-38, 40-41

FSSP 75

FTS 184

GAIM 249-252

GAP 249

gas-to-particle conversion 343-345

GCIP 20, 54-55, 91, 214, 239, 245

GCMs 48, 54, 58, 60-62, 65, 90, 102,

201, 203, 205-210, 219, 221, 12,

15, 32-33, 37-38

GCOS/GTOS TOP 237-238, 281

GCTE 246, 249-252

GEBA 70, 217, 268

GENESIS 57, 261, 268, 270, 277

GEOS 55-57, 79, 81

GERB 92

GEWEX 11, 20, 48, 54, 81, 90, 101,

214-217, 245, 251, 275, 10, 13,

22, 38

GFDL 175, 232, 251

GFO 129, 140

GGD 285

GHCN 86

GIS 238-239, 248

GISP 270

GISS 217, 280, 346

glaciers (see ice sheets)

GLAS (see also lidar) 12-13, 18-20,

24-25, 32-35, 66-69, 72, 74, 78-

79, 52, 66-69, 71-72, 74, 79, 94-

96, 101, 295, 349, 356, 358, 362-

371, 14, 17, 20, 35, 41, 49

GLCTS 241, 249

GLI 67, 69, 148, 153, 366, 24

GLIMS 278

GLOBE 216

GLOBEC 20, 132, 135-136, 150, 155

GMS 87

GNP 117

GOALS 20, 101, 149

GOES 80, 82, 87, 90, 212, 217, 239,

290

GOMOS 366

GPCP 84-86, 89, 213

GPS 141, 236, 362

GRDC 213

greenhouse forcing 311, 42

Gross Primary Production (GPP) 173

GSFC 19, 68-69, 92, 213, 215, 217,

297, 324, 333, 45

GVaP 81

F

G
60 INDEX

Page numbers in roman type can be found in the main EOS Science Plan

H2SO4 316, 320, 342-343, 345-346,

46-47

HALOE 318, 321, 323

HAPEX-Sahel 206, 238, 243

HCFC 321

HCl 342, 358-359, 364, 367, 44

health hazards, volcanic 359-361

heterogeneity 209-210

HH 176

HIRDLS 13, 18-19, 26-27, 29, 31-32,

35, 49, 78, 82, 94, 187, 208, 210,

326-332, 347, 362-363, 366-367,

18-21, 29, 44-45, 49

HIRS 21, 67-68, 78, 82, 323, 14-15

HNLC 134-135

HOx 314, 322, 325, 329

horizontal energy transport 123

HRDI 324

HSB 12-14, 21, 31-32, 35, 55, 59, 67-

71, 78-79, 82, 87, 98-99, 105,

210, 212, 217, 292, 367, 14, 17-

18, 21, 39, 41

HSCT 322

human dimensions 7, 8, 26, 34-35, 7

human health 33, 35, 169, 179

human impacts (see also ocean

economics) 154-155

humidity 8, 12, 21, 43, 43, 52, 55, 59,

77-82, 88, 92-96, 98-99, 103,

105-106, 118, 121, 138, 140,

151, 188, 204, 206-207, 217-

218, 228, 236, 247-248, 292,

350, 367, 11, 17, 21, 30, 39

hydrology 16-17, 54-55 , 156, 169,

174, 176, 181, 201, 252, 8, 28-33

IABP 297

ice mass balance 274, 277, 283, 291-

293

ice sheets 15, 17-18, 32, 34, 128-129,

263-264, 266, 269-270, 275-278,

285-287, 296-298

ICESat 278, 286, 292, 295-296, 298,

356, 371, 35, 39-40

ICRCCM 50

ICSU 237, 250

IDS (see also IDS field sites) 1-2, 15,

48, 52, 55, 59, 62-64, 79-80,

170, 185, 201-257, 331, 333,

362, 367, 24, 35

IDS field sites 238

IFOV 215

IGAC 246

IGBP 7, 20, 136, 150, 213, 216, 235,

237, 241, 246, 10

IGPPDI 251

IHP 237

ILAS 366

infiltration and deep percolation 16,

216, 33

interannual variability 11, 15-18, 20,

28-29, 43, 48, 52, 81, 89, 96,

101, 119, 124, 149-150, 152,

163, 173, 201, 208, 223, 227,

231, 241, 249, 265-268, 293,

298, 315-316, 319, 7, 11, 13, 19,

23, 28, 33, 36, 43

IOC 237

IPCC 50, 84, 136, 170, 263, 267, 271,

274, 276-277, 281-282, 311,

350-352, 370, 14-15, 22

IR 66, 81, 86-87, 95, 99, 104, 207,

234, 294, 315, 365, 368, 18

ISAMS 331, 346-347

ISCCP 49, 51-57, 59, 62, 64, 67-74,

100, 14-15, 22

ISLSCP 54, 205, 217, 243

IT 238-239

ITCZ 83-87, 212

IWP 76

Jason-1 15, 22, 24, 31, 34, 129, 140,

142, 152, 24

JERS 171, 176, 215, 288, 294, 366

JGOFS 20, 132, 135, 137, 147-149,

150, 153, 10

JPO 237

KINEROS 213

Krakatau 342, 344

LAI 16-17, 33, 172, 181, 188-206,

214, 223-233, 238, 241-244,

248, 30-31

lake ice 17, 263, 268-269, 274-275,

284, 293-295, 35-38, 40-41

land-climate interaction 201-210,

32

land cover (see land vegetation)

land cover/land-use change 168,

170-172, 181, 28-33

land ecosystems 16-17, 30, 33-34,

8, 28, 32

land hydrology 16, 201-233, 32-33

land processes 103, 23, 32

land-surface water balance 218, 33

land-vegetation 223-232, 241-243,

32

Landsat-7 23, 224-225, 234-235,

295, 34

LBA 239, 244-245

LERTS 251

LHH 176-177

lidar 52, 67, 69, 71-74, 82, 89, 94,

96, 99, 102, 178, 208, 246,

344, 347-349, 356, 367, 371,

17, 20, 22, 49

lightning 12, 23, 97, 219, 322, 15,

21

LIS 12, 62, 97, 208, 15-21

LITE (see lidar)

LOICZ 132

LS 328

LSMs 203-206, 208-210, 239, 32-

33

LSPs 201, 210, 221, 32

LTER 236-237, 248

LW 48-59, 66-72, 92, 93, 14-15

LWP 62, 66, 69, 75-76, 97, 105, 14

man-made changes 320-322

MAPS 179-182

MAPSS 224, 232, 252

marine biosphere (see also biogeochemistry) 130-138, 142-

148, 26

H

I

J

K

L

M
 INDEX 61

Page numbers in bold italics type can be found in the EOS Science Plan Executive Summary

MAAT 269

MCS 64, 76-78

measurement requirements 323-333

measurement strategy (see also

simultaneity) 21-25, 70, 284, 7,

10 overlap strategy, calibration

strategy, validation strategy,

continuity methane (CH4) 174-

176, 181-182

MERIS 67, 69, 148, 153, 366, 24

METEOR-3 26-27, 329, 347, 368

methane (CH4) 18, 22, 26-27, 29, 31-

32, 35, 49, 167-168, 181-182,

190, 222, 247-248, 314, 318, 322,

325, 329, 332, 42

METOP 66, 69, 75, 87, 98, 100, 139

MHS 21

MIMR 88, 97-100, 104-105, 139-141,

206-207, 14, 21

MISR 11-13, 17-19, 26-35, 50-54, 66-

67, 69-74, 79, 92-97, 102, 104-

105, 172, 206, 208, 210, 217,

224-227, 233-234, 288, 294, 353-

357, 362-371, 13-14, 17, 20, 34,

49

MIT 213

MLS 13, 18-19, 25-27, 29, 31, 35, 49,

77-78, 82, 97-99, 105, 313, 324-

332, 345, 363-364, 367, 18, 21,

44-45, 48-49

MMIC 326-328, 43

MMS 12, 63-65, 213

modeling 12, 20, 24, 31, 48-49, 52-54,

59-64, 72, 77-80, 83-84, 89-90,

93, 99, 101-102, 105, 121, 125-

126, 129-130, 136, 149-50, 154-

156, 172, 185-190, 213-217, 224-

228, 232-252, 270, 273-278, 282,

289, 296-299, 317, 333, 345, 371,

8, 10, 13, 15, 22-24, 27-28, 33,

35, 38, 44, 49

MODIS 12, 15-19, 21-23, 25, 28-31,

50-55, 62, 66-76, 79, 92-105,

132-139, 141-148, 152-153, 168,

171-172, 184, 208, 210, 213-214,

217, 220, 223-229, 231-233, 272,

284, 288, 291-295, 298, 353, 356,

362-370, 14, 17, 19-20, 24, 27,

29, 33-35, 37, 39-41, 49

MODLAND 248

MODLERS 248

momentum exchange 119-121, 25

MOPITT 16, 22, 26, 31, 35, 49, 167,

179, 181-183, 187, 232, 29

MOU 237

Mt. Katmai 342

Mt. Pinatubo 343-348, 361, 366-367,

371, 12, 47-48

Mt. Saint Helens 344

MSG 92

MSU 323, 343-344

MVI 228, 233

NAD 326-329

NADW 123

NASA 7, 15, 19, 43, 54, 66, 89-90,

139-140, 215-217, 236, 299, 324,

326, 328, 333, 366, 44

NASDA 23, 69, 88, 139-140

NAT 320, 326-329

National Snow and Ice Data Center

299

natural changes 319-320, 42-43

natural variability 28-31, 40

NBIOME 240

NCAR 63, 251, 271, 318

NCDC 86

NCEP 81

NDVI (see vegetation indices) 172-

173, 214, 223, 233, 34

near-surface meteorology 217-218, 33

NESDIS 282, 288

Nevada del Ruiz 344

NEXRAD 86, 212, 239

NH 280, 283

Nimbus-7 311

NIR 223, 226, 294

nitric oxide (NO) 16, 177-178, 28-29

nitrous oxide (N2O) 9, 15-16, 29, 168,

170, 177-178, 28-29

NMC 81, 89, 91, 210

NMHCs 178-179, 188, 31

NOAA 21, 23, 26-27, 67-68, 78, 81,

86-87, 90, 102, 206, 212, 217,

227, 236, 241, 247, 250, 281-283,

288, 323-324, 328, 368, 14, 15,

40

NOPEX 245-246

NOx 167-168, 177-179, 314, 319, 322,

325, 329, 350

NPOESS 324, 330

NPP 16-17, 33, 170, 173, 223, 227-

229, 241-242, 249-251, 30, 33

NRC 7, 219

NSCAT 28, 120, 139, 152

NSF 236, 241, 245, 285, 297-298

NSIDC 299

NWP 54, 81, 274, 287-290

ocean-atmosphere surface coupling

118-123, 25

ocean carbon (see marine biosphere;

see also CO2 fluxes) 169-170,

173-174, 28-29

ocean circulation (see also Jason-1) 14-

15, 24, 118-119, 123-130, 134-

140, 140-141, 147-156, 8, 13, 24-

26

ocean color 15, 23, 28, 34, 131, 133,

143-148, 153-156, 167, 174, 188,

341, 366, 23-24, 30

ocean economics (see also human

impacts) 117

ocean food stocks 132

ocean surface topography 22

ocean tides (see also sea level) 128-

130, 142, 154

oceanic processes 99-101

OCS 316, 329

OCTS 153, 366, 24

OH 182-183, 314, 321, 325-326, 329,

332, 44-47

OLR 49, 53-56, 93, 279-281, 344, 39

OMI 19, 25, 326, 329-332, 350, 355-

356, 363-365, 49

ONR 297

N

O
62 INDEX

Page numbers in roman type can be found in the main EOS Science Plan

ORNL 251

OSU 137, 175, 232, 251-252

OTTER 228, 243-244

overlap strategy 21-22, 10

ozone (see tropospheric ozone, see

ozone precursors) 18-19, 25-28,

8, 28-29, 42-44, 47

ozone changes (see also man-made

change, natural changes) 312-

315

ozone chemistry 314-315

ozone distribution (see also natural

changes, man-made changes)

314, 317, 319-320

ozone precursors 178-181, 183

ozone transport 315

PAR 142, 144, 204, 214, 226, 228,

233, 247, 265, 267, 36

PARCA 297

Pathfinder data 54

PEM 228

PIK-NPP 232, 250-252

PILPS 251

phytoplankton 118, 132-137, 143-148,

153-155, 27

PNZ 137

POLDER 66, 69, 73-76, 208, 366

POLES 299

policy-relevant questions 9

PR 14, 87, 207, 212, 18, 21

precipitation 13-14, 43-106, 138, 140-

141, 151-155, 211-213, 233, 236-

243, 247-249, 263, 266, 268,

270-273, 280-283, 319, 343-344,

8, 11, 14, 16, 18-19, 21, 23, 25-

26, 32-33, 35

precision orbit determination (see sea

level)

productivity 117-156, 8, 24, 26-27, 29,

32, 36

PSC 315-316, 318-322, 325, 327, 331,

43, 44

PSU 63, 213, 217

QBO 315, 319, 322, 344

QuikSCAT 14, 24, 89, 139, 19, 21

RADARSAT 176, 215, 241, 278, 282-

283, 285, 288, 291-296, 359, 364,

366, 39

radiation 216-217, 8, 11-16, 18-23, 25,

27, 29-30, 33-39, 42-43, 47-49

radiation fluxes 11-12

radiation in climate models 55

RAMS 63-64

RC 48

reactive nitrogen (see also nitric oxide

and nitrous oxide) 178

REP 317

RGPS 283

river ice 268-269, 35-36

runoff 213, 25, 33, 37-40

SAFARI 181

SAGE 313, 331, 350, 44-45, 49

SAGE II 347, 14

SAGE III 19, 26-27, 31, 78-79, 82, 94-

99, 105, 208, 210, 313, 330-332,

347, 363, 367, 18, 20-21, 44-45,

49

salinity 83, 123, 125-126, 129, 138,

140, 143, 151-155, 359

SALSA 216, 238

SAM 316-317, 347, 349

SAR 176-177, 213, 221, 236, 241, 264,

273, 275, 278, 282-298, 362, 364,

37, 40-41

satellite measurements 87-89, 91, 99,

128, 137-140, 150, 14, 19, 22, 45

SAVI 226

SBUV 313-314

SCA 266-267, 272, 282-290

SCANSAR 366

SCARAB 67-68, 14-15

SCF 363

SCICEX 297

SCOPE 250

sea ice 25, 267-268, 273-274, 283-284,

291-293, 25, 35-40

sea level (see also Jason-1) 24, 31,

117-156, 25-26, 35, 37

SeaWiFs 15, 28, 135, 145, 153, 8, 24,

38

SeaWinds 14-15, 24, 28, 31, 88, 99,

100, 139, 141, 151-152, 19, 21,

24

SEB 138-139, 150, 152, 264, 271, 279-

280, 284, 291, 298

SEDAC 174

SHEBA 20, 297

SiB 53, 201, 203, 239

SIMIP 274

SLR 130, 142

SMM 23, 43-47

SMMR 75, 81, 87, 177, 215, 40

snow cover 17-18, 25-35, 83, 177, 207,

211, 240, 263-267, 271-273, 281-

283, 287, 13, 35-40

snow-water equivalence 267, 272-273,

281-290, 295, 297, 37, 40

SOHO 44-47

soil moisture (see also wetlands) 169,

176-177, 215-216, 28-33

soils data 216, 235-236

SOLAS 150

SOLSTICE 22, 31, 144, 326, 330-331,

44

SPCZ 85

SPOT 148, 171, 294, 333

SRB (see Earth’s surface absorption)

11-12, 54, 67-68, 204 13-15

SRBEX 239

SSM/I 25, 67-68, 75-76, 81, 87-88,

139-140, 177, 215, 239-240, 282,

288, 294-296, 14-15, 40-41

SST 15, 23-25, 28, 32, 58, 60-61, 65,

80, 86-89, 100, 103, 219-221,

241, 18, 24, 30

SST measurements 121, 126, 132, 138-

139

P

Q

R

S
 INDEX 63

Page numbers in bold italics type can be found in the EOS Science Plan Executive Summary

stem and soil carbon 229-230

steric change (see sea level)

STP 184, 312

sulfate (see SO2) 11, 19, 26, 29, 31, 50,

319-320, 329, 341-352, 359, 365,

370-371, 13, 47

sulfur (see also SO2) 19, 26, 50, 174,

322, 341-343, 351, 46-49

sulfur dioxide (SO2) 19, 26-29, 316,

319, 329-332, 341-346, 350-354,

358-359, 365, 367-368, 46-48

sulfuric acid 316, 320, 342-343, 345-

346, 46-47

surface energy balance (SEB) (see also

Earth’s surface absorption) 270,

279, 280, 291, 38 clouds effect

on 56-57

surface flux 70, 72, 102, 118, 125, 142,

151-153

surface flux measurements 137-138

surface forcing 102, 126, 129, 132, 142

surface insolation 49

surface observations 58, 74, 86, 99,

101, 149, 152, 177, 215, 29

SVAT 54

SVI 228

SW 48-59, 66-71, 92-93, 267, 279-280,

347, 14-15

SWE 212-213, 240, 290

SWIR 234, 295-296, 365, 369-370

Synthetic Aperture Radar (SAR) 176

T-S 125-126

Tambora 342, 344, 47

TARFOX 353

TEM 175, 225, 229, 232, 240, 251

temperature profiles 81, 97, 99, 21, 45

TES 49-50, 96, 183, 187, 29, 49

thermal fluxes 121, 25

thermohaline circulation 121-126, 25

THM 213

tides (see sea level, see also ocean

tides)

T

TIR 215, 234, 294, 296, 362, 365

TM 221, 234-235, 241, 249, 284-290,

295-296, 40-41

TMI 14, 67-68, 75, 87-88, 207, 212,

14-15, 18

TOA 11-12, 21, 25, 217, 12, 14, 16-17,

20

TOGA 63-64, 83, 101, 140, 149, 152

TOMS 19, 25-27, 311-314, 326, 329-

331, 356, 365, 367-369, 49

TOPEX/Poseidon 22-23, 28, 129-131,

140, 142, 152

topography 22, 64, 124, 129, 140-144,

149, 202, 212, 221-222, 229,

234-236, 243, 271-273, 277-278,

286-289, 295-296, 361-367, 48-

49

TOPSAR 236, 361

TOVS 21, 78-81, 298, 323-324, 331

tower sites 246

trace-gas exchange (see marine

biosphere)

trace gases 11, 20, 27, 31, 48-49, 156,

167-168, 170, 172, 178, 182-190,

317, 319, 328, 333, 350-351, 29,

31

TRAGNET 246-247

TRMM 12, 14, 23, 65-70, 75, 87, 92,

94, 97, 99, 101, 104-105, 140,

212, 15-16, 18, 20-21, 26

tropospheric ozone (O3) 168-169, 178-

181, 28

TSI 8, 11, 22, 29, 31, 43-47, 103, 12

UARS 313, 318-321, 323, 326-332, 12,

14, 44

UKMO 175, 232, 251

UMCP 251

UNEP 237

UNESCO 237

USAF 289

USDA 238-239

USGCRP 7-9, 20, 26, 26, 55, 102, 7-8,

10, 22

USGS 54, 213, 250

UT 328

U

V

UV 311, 327, 330-331, 42-43

UV-B 311, 330

validation 12-13, 18, 24, 29, 49, 54-55,

59-60, 64-75, 81-82, 86, 90-94,

99, 101-104, 146, 152, 155, 174,

201, 204-208, 213-216, 229, 234-

252, 272, 274-275, 281-282, 287,

289-291, 297, 299, 327, 349, 366,

370, 8, 15-17, 22

validation strategy 24

variability, trend detection 105

VCL 19-20

vegetation indices 16-17, 202, 207-

208, 223, 226-227, 33-34

vegetation phenology 203, 223, 227,

234, 242, 33

vegetation structure 241-243

VEMAP 174-175, 214, 218, 229, 232,

236, 239, 240, 251-252

vertical circulation 135

VHRR 281

VI (see vegetation indices)

VIC 213

VIRGO 44, 46-47

VIRS 52, 66-76, 87, 92, 94, 207, 212,

14-15, 17-18, 20

VIS 14, 87, 104, 223, 226, 294, 18

VNIR 234, 295-296

VOC 350-351

volcanic detection 360-362, 368

volcanic eruptions (see specific event

names)

volcanic hazards 358-362, 367, 8, 46-

48

volcanic measurements, international

368

volcanoes 18-20, 22, 26, 29, 31, 206,

316, 322, 341-372, 8, 46, 48

water-leaving radiance 144

water transparency 147-148

W
64 INDEX

Page numbers in roman type can be found in the main EOS Science Plan

Y

water vapor 8, 11-16, 19-22, 25, 29,

32, 36, 43-106, 342-345, 350,

352, 358, 362, 364, 368, 8, 11,

13-14, 17-23, 33

WCRP 20, 51, 70-74, 90, 101-103,

204, 213, 237, 241, 245, 251,

274, 281, 288, 22, 39-40

WDC-A 293, 297, 299

wetlands (see also soil moisture) 176-

177, 28, 38

WFPS 178

wind 13-15, 19-24, 29, 34, 48, 55, 79,

88-89, 99-105, 117-156, 167,

173, 174, 181, 187-188, 206-207,

217, 219-220, 248, 269, 272, 312,

319, 323-324, 333, 341, 344, 367,

370, 19-24, 30, 38, 44-46

wind fields 121, 142-143, 45

wind stress 181, 23-25, 30

WMO 237, 311, 316-318, 320-321,

324

WOCE 30, 101, 131, 149, 152-153

WSR 86, 212, 245, 316

year without a summer 342
January 1999 NP-1998-12-070-G

National Aeronautics and

Space Administration